
R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> source("pscore_estimation_core1.R")
Loading required package: gbm
Loading required package: survival
Loading required package: splines
Loading required package: lattice
Loaded gbm 1.6-3.1 
Loading required package: survey

Attaching package: 'survey'

The following object(s) are masked from 'package:graphics':

    dotchart

Loading required package: xtable
Loading required package: MASS
Loading required package: mlbench
Loading required package: nnet
Loading required package: class

Attaching package: 'ipred'

The following object(s) are masked from 'package:survey':

    cv

randomForest 4.5-36
Type rfNews() to see new features/changes/bug fixes.
> library(Matching)
Loading required package: rgenoud
##  rgenoud (Version 5.6-7, Build Date: 2010-06-01)
##  See http://sekhon.berkeley.edu/rgenoud for additional documentation.
## 
##  Matching (Version 4.7-10, Build Date: 2010/08/13)
##  See http://sekhon.berkeley.edu/matching for additional documentation.
##  Please cite software as:
##   Jasjeet S. Sekhon. Forthcoming. ``Multivariate and Propensity Score Matching
##   Software with Automated Balance Optimization: The Matching package for R.''
##   Journal of Statistical Software. 
##
> 
> load(file="RData.simdata.G.obs1000.reps1000")
> dta <- simdata.G.obs1000.reps1000
> rm(simdata.G.obs1000.reps1000)
> gc()
           used (Mb) gc trigger  (Mb) max used (Mb)
Ncells   200675 10.8     407500  21.8   350000 18.7
Vcells 12195008 93.1   13300721 101.5 12195672 93.1
> 
> #true estimate
> g1 <- -0.4
> 
> sims <- dim(dta)[2]
> nobs <- length(dta[1,2]$w1)
> 
> true.est <- matrix(0, nrow=sims, ncol=1)
> 
> logit.pscore <- list()
> logit.est <- matrix(0, nrow=sims, ncol=1)
> logit.nSE <- matrix(0, nrow=sims, ncol=1)
> logit.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> boosting.pscore <- list()
> boosting.desc <- list()
> boosting.est <- matrix(0, nrow=sims, ncol=1)
> boosting.nSE <- matrix(0, nrow=sims, ncol=1)
> boosting.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> forest.pscore <- list()
> forest.est <- matrix(0, nrow=sims, ncol=1)
> forest.nSE <- matrix(0, nrow=sims, ncol=1)
> forest.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> nnet.pscore <- list()
> nnet.est <- matrix(0, nrow=sims, ncol=1)
> nnet.nSE <- matrix(0, nrow=sims, ncol=1)
> nnet.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> count <- 0
> for (s in 1:sims)
+   {
+     cat("\n\ns:",s,"\n")
+     count <- count+1
+ 
+     sdta <- as.data.frame(dta[,s])
+ 
+     #true model
+ #    lm1 <- lm(y.a~ z.a+ w1 + w2 + w3 + w4 + w8 + w9 + w10, data=sdta)
+ #    true.est[s] <- lm1$coef[2]
+ #    cat("truth:",mean(true.est[1:s]),"\n")
+ 
+     #logit
+     logit.ps <- glm(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, data=sdta, family=binomial(link="logit"))$fitted
+     logit.pscore[[s]] <- logit.ps
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=logit.ps, estimand="ATT", M=1)
+     logit.est[s] <-  m1$est
+     logit.nSE[s] <- m1$se.standard
+     logit.aiSE[s] <- m1$se
+ 
+     cat("logit",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("logit mean",s,":",mean(logit.est[1:s]),"\n")
+         rmse <- sqrt(mean((logit.est[1:s]-g1)^2))
+         cat("logit RMSE",s,":",rmse,"\n")
+       }
+ 
+     #boosting!
+     ps.model <- ps(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10,
+                    data=sdta, title="none", stop.method=stop.methods["ks.stat.mean"],
+                    plots="none", pdf.plots=F, n.trees=20000, interaction.depth=4,
+                    shrinkage=0.0005, verbose=FALSE)
+ 
+     boosting.pscore[[s]] <- ps.model$ps
+     boosting.desc[[s]] <- ps.model$desc
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=ps.model$ps, estimand="ATT", M=1)
+     boosting.est[s] <-  m1$est
+     boosting.nSE[s] <- m1$se.standard
+     boosting.aiSE[s] <- m1$se
+ 
+     cat("\nboosting",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("boosting mean",s,":",mean(boosting.est[1:s]),"\n")
+         rmse <- sqrt(mean((boosting.est[1:s]-g1)^2))
+         cat("boosting RMSE",s,":",rmse,"\n")
+       }    
+ 
+ 
+     #Random Forest
+     ps1 <- 1
+     while (max(ps1)> .999) {
+ #      gc(verbose=TRUE)
+       fps.model <- randomForest(as.factor(z.a) ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, data=sdta)
+       ps1 <- fps.model$votes[, 2]
+     }
+     
+     forest.pscore[[s]] <- ps1
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=ps1, estimand="ATT", M=1)
+     forest.est[s] <-  m1$est
+     forest.nSE[s] <- m1$se.standard
+     forest.aiSE[s] <- m1$se
+ 
+     cat("\nforest",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("forest mean",s,":",mean(forest.est[1:s]),"\n")
+         rmse <- sqrt(mean((forest.est[1:s]-g1)^2))
+         cat("forest RMSE",s,":",rmse,"\n")
+       }
+ 
+     n1 <- nnet(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, size=40, data=sdta, trace=FALSE)
+     nnet.pscore[[s]] <- n1$fitted.values
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=n1$fitted.values, estimand="ATT", M=1)
+     nnet.est[s] <-  m1$est
+     nnet.nSE[s] <- m1$se.standard
+     nnet.aiSE[s] <- m1$se
+ 
+     cat("\nnnet",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("nnet mean",s,":",mean(nnet.est[1:s]),"\n")
+         rmse <- sqrt(mean((nnet.est[1:s]-g1)^2))
+         cat("nnet RMSE",s,":",rmse,"\n")
+       }    
+ 
+     if (count>50)
+       {
+         save.image("RData.sims.G.nobs1000")
+         count <- 0
+       }
+   }#end of sims loop


s: 1 
logit 1 : -0.5230348 

boosting 1 : -0.527247 

forest 1 : -0.3451724 

nnet 1 : -0.5537023 


s: 2 
logit 2 : -0.4570072 
logit mean 2 : -0.490021 
logit RMSE 2 : 0.09588371 

boosting 2 : -0.3605246 
boosting mean 2 : -0.4438858 
boosting RMSE 2 : 0.0942075 

forest 2 : -0.4998457 
forest mean 2 : -0.422509 
forest RMSE 2 : 0.08054575 

nnet 2 : -0.5896533 
nnet mean 2 : -0.5716778 
nnet RMSE 2 : 0.1726163 


s: 3 
logit 3 : -0.5084374 
logit mean 3 : -0.4961598 
logit RMSE 3 : 0.1002431 

boosting 3 : -0.5296737 
boosting mean 3 : -0.4724818 
boosting RMSE 3 : 0.1073396 

forest 3 : -0.4062896 
forest mean 3 : -0.4171026 
forest RMSE 3 : 0.06586551 

nnet 3 : -0.2155122 
nnet mean 3 : -0.4529560 
nnet RMSE 3 : 0.1766621 


s: 4 
logit 4 : -0.3662078 
logit mean 4 : -0.4636718 
logit RMSE 4 : 0.08844202 

boosting 4 : -0.1738341 
boosting mean 4 : -0.3978199 
boosting RMSE 4 : 0.1463868 

forest 4 : -0.3234171 
forest mean 4 : -0.3936812 
forest RMSE 4 : 0.06870178 

nnet 4 : -0.5225245 
nnet mean 4 : -0.4703481 
nnet RMSE 4 : 0.1648035 


s: 5 
logit 5 : -0.4478066 
logit mean 5 : -0.4604987 
logit RMSE 5 : 0.08194319 

boosting 5 : -0.5031028 
boosting mean 5 : -0.4188764 
boosting RMSE 5 : 0.1388139 

forest 5 : -0.4749097 
forest mean 5 : -0.4099269 
forest RMSE 5 : 0.06998744 

nnet 5 : -0.4367673 
nnet mean 5 : -0.4636319 
nnet RMSE 5 : 0.1483190 


s: 6 
logit 6 : -0.4573808 
logit mean 6 : -0.4599791 
logit RMSE 6 : 0.07838579 

boosting 6 : -0.6972764 
boosting mean 6 : -0.4652764 
boosting RMSE 6 : 0.1754612 

forest 6 : -0.3583054 
forest mean 6 : -0.4013233 
forest RMSE 6 : 0.06611813 

nnet 6 : -0.3090432 
nnet mean 6 : -0.4378671 
nnet RMSE 6 : 0.1403957 


s: 7 
logit 7 : -0.4609024 
logit mean 7 : -0.460111 
logit RMSE 7 : 0.07613437 

boosting 7 : -0.5115426 
boosting mean 7 : -0.4718859 
boosting RMSE 7 : 0.1678271 

forest 7 : -0.3774603 
forest mean 7 : -0.3979143 
forest RMSE 7 : 0.06180347 

nnet 7 : -0.4049015 
nnet mean 7 : -0.4331578 
nnet RMSE 7 : 0.1299944 


s: 8 
logit 8 : -0.4449605 
logit mean 8 : -0.4582172 
logit RMSE 8 : 0.07296963 

boosting 8 : -0.2688788 
boosting mean 8 : -0.44651 
boosting RMSE 8 : 0.1636896 

forest 8 : -0.3468841 
forest mean 8 : -0.3915355 
forest RMSE 8 : 0.06078547 

nnet 8 : -0.6253999 
nnet mean 8 : -0.457188 
nnet RMSE 8 : 0.1453852 


s: 9 
logit 9 : -0.4705432 
logit mean 9 : -0.4595867 
logit RMSE 9 : 0.07270403 

boosting 9 : -0.4720441 
boosting mean 9 : -0.4493471 
boosting RMSE 9 : 0.1561853 

forest 9 : -0.4467975 
forest mean 9 : -0.3976758 
forest RMSE 9 : 0.05939416 

nnet 9 : -0.3631724 
nnet mean 9 : -0.4467418 
nnet RMSE 9 : 0.1376191 


s: 10 
logit 10 : -0.5217942 
logit mean 10 : -0.4658075 
logit RMSE 10 : 0.07899791 

boosting 10 : -0.3056586 
boosting mean 10 : -0.4349783 
boosting RMSE 10 : 0.1511440 

forest 10 : -0.4228981 
forest mean 10 : -0.400198 
forest RMSE 10 : 0.0568096 

nnet 10 : -0.3049433 
nnet mean 10 : -0.432562 
nnet RMSE 10 : 0.1339727 


s: 11 
logit 11 : -0.4920646 
logit mean 11 : -0.4681945 
logit RMSE 11 : 0.08027374 

boosting 11 : -0.4435869 
boosting mean 11 : -0.4357609 
boosting RMSE 11 : 0.1447081 

forest 11 : -0.3900972 
forest mean 11 : -0.3992797 
forest RMSE 11 : 0.05424806 

nnet 11 : -0.4088049 
nnet mean 11 : -0.4304023 
nnet RMSE 11 : 0.1277656 


s: 12 
logit 12 : -0.4421244 
logit mean 12 : -0.466022 
logit RMSE 12 : 0.07781231 

boosting 12 : -0.4692329 
boosting mean 12 : -0.4385502 
boosting RMSE 12 : 0.1399816 

forest 12 : -0.4859588 
forest mean 12 : -0.406503 
forest RMSE 12 : 0.05756178 

nnet 12 : -0.2810268 
nnet mean 12 : -0.4179543 
nnet RMSE 12 : 0.1270561 


s: 13 
logit 13 : -0.5193451 
logit mean 13 : -0.4701238 
logit RMSE 13 : 0.08175965 

boosting 13 : -0.3493089 
boosting mean 13 : -0.4316855 
boosting RMSE 13 : 0.1352228 

forest 13 : -0.4179916 
forest mean 13 : -0.4073867 
forest RMSE 13 : 0.05552823 

nnet 13 : -0.4602275 
nnet mean 13 : -0.4212061 
nnet RMSE 13 : 0.1232091 


s: 14 
logit 14 : -0.6036023 
logit mean 14 : -0.4796579 
logit RMSE 14 : 0.0957505 

boosting 14 : -0.4437974 
boosting mean 14 : -0.4325506 
boosting RMSE 14 : 0.1308286 

forest 14 : -0.5036664 
forest mean 14 : -0.4142639 
forest RMSE 14 : 0.06025584 

nnet 14 : -0.5416629 
nnet mean 14 : -0.4298101 
nnet RMSE 14 : 0.1246179 


s: 15 
logit 15 : -0.4805938 
logit mean 15 : -0.4797203 
logit RMSE 15 : 0.09481546 

boosting 15 : -0.6428737 
boosting mean 15 : -0.4465722 
boosting RMSE 15 : 0.1410942 

forest 15 : -0.3995142 
forest mean 15 : -0.4132805 
forest RMSE 15 : 0.0582128 

nnet 15 : -0.2602680 
nnet mean 15 : -0.4185073 
nnet RMSE 15 : 0.1256821 


s: 16 
logit 16 : -0.5298732 
logit mean 16 : -0.4828549 
logit RMSE 16 : 0.09737705 

boosting 16 : -0.4664049 
boosting mean 16 : -0.4478117 
boosting RMSE 16 : 0.1376188 

forest 16 : -0.480823 
forest mean 16 : -0.4175019 
forest RMSE 16 : 0.0598766 

nnet 16 : -0.460795 
nnet mean 16 : -0.4211503 
nnet RMSE 16 : 0.1226366 


s: 17 
logit 17 : -0.4798027 
logit mean 17 : -0.4826754 
logit RMSE 17 : 0.09643197 

boosting 17 : -0.4208679 
boosting mean 17 : -0.4462268 
boosting RMSE 17 : 0.1336058 

forest 17 : -0.4101731 
forest mean 17 : -0.4170708 
forest RMSE 17 : 0.05814121 

nnet 17 : -0.2588175 
nnet mean 17 : -0.4116013 
nnet RMSE 17 : 0.1238045 


s: 18 
logit 18 : -0.40227 
logit mean 18 : -0.4782084 
logit RMSE 18 : 0.09371655 

boosting 18 : -0.7003053 
boosting mean 18 : -0.4603423 
boosting RMSE 18 : 0.1478817 

forest 18 : -0.4927817 
forest mean 18 : -0.421277 
forest RMSE 18 : 0.06058752 

nnet 18 : -0.1827612 
nnet mean 18 : -0.398888 
nnet RMSE 18 : 0.1307587 


s: 19 
logit 19 : -0.4066618 
logit mean 19 : -0.4744428 
logit RMSE 19 : 0.0912298 

boosting 19 : -0.3628082 
boosting mean 19 : -0.4552089 
boosting RMSE 19 : 0.1441901 

forest 19 : -0.3558448 
forest mean 19 : -0.4178332 
forest RMSE 19 : 0.05983527 

nnet 19 : -0.3161069 
nnet mean 19 : -0.3945311 
nnet RMSE 19 : 0.1287182 


s: 20 
logit 20 : -0.3498791 
logit mean 20 : -0.4682146 
logit RMSE 20 : 0.0896233 

boosting 20 : -0.4063592 
boosting mean 20 : -0.4527664 
boosting RMSE 20 : 0.1405463 

forest 20 : -0.5054857 
forest mean 20 : -0.4222158 
forest RMSE 20 : 0.06290952 

nnet 20 : -0.3566554 
nnet mean 20 : -0.3926373 
nnet RMSE 20 : 0.1258328 


s: 21 
logit 21 : -0.4888956 
logit mean 21 : -0.4691994 
logit RMSE 21 : 0.08958879 

boosting 21 : -0.4641842 
boosting mean 21 : -0.4533101 
boosting RMSE 21 : 0.1378725 

forest 21 : -0.3403061 
forest mean 21 : -0.4183154 
forest RMSE 21 : 0.06276013 

nnet 21 : -0.4680278 
nnet mean 21 : -0.3962273 
nnet RMSE 21 : 0.1236943 


s: 22 
logit 22 : -0.4536531 
logit mean 22 : -0.4684928 
logit RMSE 22 : 0.08827329 

boosting 22 : -0.382569 
boosting mean 22 : -0.4500946 
boosting RMSE 22 : 0.1347538 

forest 22 : -0.4166789 
forest mean 22 : -0.418241 
forest RMSE 22 : 0.0614202 

nnet 22 : -0.3684927 
nnet mean 22 : -0.3949667 
nnet RMSE 22 : 0.1210369 


s: 23 
logit 23 : -0.4619745 
logit mean 23 : -0.4682094 
logit RMSE 23 : 0.08729477 

boosting 23 : -0.6395532 
boosting mean 23 : -0.4583319 
boosting RMSE 23 : 0.1409401 

forest 23 : -0.5037358 
forest mean 23 : -0.4219581 
forest RMSE 23 : 0.06384588 

nnet 23 : -0.2993530 
nnet mean 23 : -0.3908095 
nnet RMSE 23 : 0.1202223 


s: 24 
logit 24 : -0.6277233 
logit mean 24 : -0.4748558 
logit RMSE 24 : 0.09728107 

boosting 24 : -0.7907426 
boosting mean 24 : -0.4721824 
boosting RMSE 24 : 0.1593678 

forest 24 : -0.496593 
forest mean 24 : -0.4250679 
forest RMSE 24 : 0.06553785 

nnet 24 : -0.5206334 
nnet mean 24 : -0.3962189 
nnet RMSE 24 : 0.1202394 


s: 25 
logit 25 : -0.4810794 
logit mean 25 : -0.4751047 
logit RMSE 25 : 0.09668514 

boosting 25 : -0.5876031 
boosting mean 25 : -0.4767992 
boosting RMSE 25 : 0.1605926 

forest 25 : -0.5398222 
forest mean 25 : -0.4296581 
forest RMSE 25 : 0.07003864 

nnet 25 : -0.2468698 
nnet mean 25 : -0.3902449 
nnet RMSE 25 : 0.1217258 


s: 26 
logit 26 : -0.5132405 
logit mean 26 : -0.4765715 
logit RMSE 26 : 0.09737395 

boosting 26 : -0.5156868 
boosting mean 26 : -0.4782949 
boosting RMSE 26 : 0.1591000 

forest 26 : -0.4668827 
forest mean 26 : -0.4310898 
forest RMSE 26 : 0.0699199 

nnet 26 : -0.2754684 
nnet mean 26 : -0.3858304 
nnet RMSE 26 : 0.1218349 


s: 27 
logit 27 : -0.5409847 
logit mean 27 : -0.4789572 
logit RMSE 27 : 0.0993312 

boosting 27 : -0.3815502 
boosting mean 27 : -0.4747118 
boosting RMSE 27 : 0.1561663 

forest 27 : -0.3986704 
forest mean 27 : -0.4298891 
forest RMSE 27 : 0.06861334 

nnet 27 : -0.3795151 
nnet mean 27 : -0.3855965 
nnet RMSE 27 : 0.1196224 


s: 28 
logit 28 : -0.4586835 
logit mean 28 : -0.4782331 
logit RMSE 28 : 0.09816973 

boosting 28 : -0.3629415 
boosting mean 28 : -0.47072 
boosting RMSE 28 : 0.1535120 

forest 28 : -0.3615503 
forest mean 28 : -0.4274484 
forest RMSE 28 : 0.06776765 

nnet 28 : -0.5455066 
nnet mean 28 : -0.3913076 
nnet RMSE 28 : 0.1206425 


s: 29 
logit 29 : -0.4260165 
logit mean 29 : -0.4764325 
logit RMSE 29 : 0.0965832 

boosting 29 : -0.2444916 
boosting mean 29 : -0.462919 
boosting RMSE 29 : 0.1535813 

forest 29 : -0.4347276 
forest mean 29 : -0.4276994 
forest RMSE 29 : 0.06690053 

nnet 29 : -0.696604 
nnet mean 29 : -0.4018351 
nnet RMSE 29 : 0.1307147 


s: 30 
logit 30 : -0.4801695 
logit mean 30 : -0.4765571 
logit RMSE 30 : 0.09608126 

boosting 30 : -0.7453594 
boosting mean 30 : -0.4723337 
boosting RMSE 30 : 0.1636360 

forest 30 : -0.3740443 
forest mean 30 : -0.4259109 
forest RMSE 30 : 0.06594655 

nnet 30 : -0.220445 
nnet mean 30 : -0.3957887 
nnet RMSE 30 : 0.1326327 


s: 31 
logit 31 : -0.5009934 
logit mean 31 : -0.4773454 
logit RMSE 31 : 0.09624363 

boosting 31 : -0.6983445 
boosting mean 31 : -0.4796243 
boosting RMSE 31 : 0.1696592 

forest 31 : -0.4791044 
forest mean 31 : -0.4276268 
forest RMSE 31 : 0.0664117 

nnet 31 : -0.5126881 
nnet mean 31 : -0.3995597 
nnet RMSE 31 : 0.1320364 


s: 32 
logit 32 : -0.4856715 
logit mean 32 : -0.4776055 
logit RMSE 32 : 0.0959309 

boosting 32 : -0.5898208 
boosting mean 32 : -0.483068 
boosting RMSE 32 : 0.1703254 

forest 32 : -0.4116306 
forest mean 32 : -0.427127 
forest RMSE 32 : 0.06539811 

nnet 32 : -0.2341670 
nnet mean 32 : -0.3943912 
nnet RMSE 32 : 0.1332224 


s: 33 
logit 33 : -0.4149133 
logit mean 33 : -0.4757058 
logit RMSE 33 : 0.09450188 

boosting 33 : -0.3711836 
boosting mean 33 : -0.4796775 
boosting RMSE 33 : 0.1677999 

forest 33 : -0.3955994 
forest mean 33 : -0.4261716 
forest RMSE 33 : 0.06440417 

nnet 33 : -0.569309 
nnet mean 33 : -0.3996917 
nnet RMSE 33 : 0.1344583 


s: 34 
logit 34 : -0.479087 
logit mean 34 : -0.4758052 
logit RMSE 34 : 0.09408455 

boosting 34 : -0.4009134 
boosting mean 34 : -0.4773609 
boosting RMSE 34 : 0.1653139 

forest 34 : -0.401196 
forest mean 34 : -0.425437 
forest RMSE 34 : 0.06345031 

nnet 34 : -0.2806634 
nnet mean 34 : -0.3961909 
nnet RMSE 34 : 0.1340379 


s: 35 
logit 35 : -0.4906178 
logit mean 35 : -0.4762284 
logit RMSE 35 : 0.09398728 

boosting 35 : -0.4988887 
boosting mean 35 : -0.477976 
boosting RMSE 35 : 0.1637903 

forest 35 : -0.3812945 
forest mean 35 : -0.4241758 
forest RMSE 35 : 0.06261719 

nnet 35 : -0.1333399 
nnet mean 35 : -0.3886808 
nnet RMSE 35 : 0.1395868 


s: 36 
logit 36 : -0.3156741 
logit mean 36 : -0.4717686 
logit RMSE 36 : 0.09373236 

boosting 36 : -0.4478969 
boosting mean 36 : -0.4771405 
boosting RMSE 36 : 0.1616966 

forest 36 : -0.3997504 
forest mean 36 : -0.4234973 
forest RMSE 36 : 0.06174139 

nnet 36 : -0.4949392 
nnet mean 36 : -0.3916325 
nnet RMSE 36 : 0.1385410 


s: 37 
logit 37 : -0.450591 
logit mean 37 : -0.4711962 
logit RMSE 37 : 0.09283036 

boosting 37 : -0.4664801 
boosting mean 37 : -0.4768524 
boosting RMSE 37 : 0.1598705 

forest 37 : -0.5136591 
forest mean 37 : -0.4259341 
forest RMSE 37 : 0.06370336 

nnet 37 : -0.5672685 
nnet mean 37 : -0.3963794 
nnet RMSE 37 : 0.1393953 


s: 38 
logit 38 : -0.4529164 
logit mean 38 : -0.4707152 
logit RMSE 38 : 0.09200211 

boosting 38 : -0.2581551 
boosting mean 38 : -0.4710972 
boosting RMSE 38 : 0.1594223 

forest 38 : -0.5143328 
forest mean 38 : -0.4282604 
forest RMSE 38 : 0.06553873 

nnet 38 : -0.3337424 
nnet mean 38 : -0.394731 
nnet RMSE 38 : 0.1379683 


s: 39 
logit 39 : -0.4288134 
logit mean 39 : -0.4696408 
logit RMSE 39 : 0.09093206 

boosting 39 : -0.2531364 
boosting mean 39 : -0.4655084 
boosting RMSE 39 : 0.1591127 

forest 39 : -0.3827269 
forest mean 39 : -0.4270929 
forest RMSE 39 : 0.06475213 

nnet 39 : -0.3722873 
nnet mean 39 : -0.3941556 
nnet RMSE 39 : 0.1362602 


s: 40 
logit 40 : -0.4155487 
logit mean 40 : -0.4682885 
logit RMSE 40 : 0.08982187 

boosting 40 : -0.2617394 
boosting mean 40 : -0.4604142 
boosting RMSE 40 : 0.1586248 

forest 40 : -0.4162996 
forest mean 40 : -0.426823 
forest RMSE 40 : 0.06398953 

nnet 40 : -0.2618338 
nnet mean 40 : -0.3908475 
nnet RMSE 40 : 0.1363082 


s: 41 
logit 41 : -0.4590358 
logit mean 41 : -0.4680628 
logit RMSE 41 : 0.0891975 

boosting 41 : -0.4163349 
boosting mean 41 : -0.4593391 
boosting RMSE 41 : 0.1566991 

forest 41 : -0.3581057 
forest mean 41 : -0.425147 
forest RMSE 41 : 0.0635421 

nnet 41 : -0.4577816 
nnet mean 41 : -0.3924801 
nnet RMSE 41 : 0.1349377 


s: 42 
logit 42 : -0.4075332 
logit mean 42 : -0.4666216 
logit RMSE 42 : 0.0881369 

boosting 42 : -0.6706441 
boosting mean 42 : -0.4643702 
boosting RMSE 42 : 0.1603558 

forest 42 : -0.459247 
forest mean 42 : -0.4259589 
forest RMSE 42 : 0.06344321 

nnet 42 : -0.6015231 
nnet mean 42 : -0.3974573 
nnet RMSE 42 : 0.1369000 


s: 43 
logit 43 : -0.4691958 
logit mean 43 : -0.4666815 
logit RMSE 43 : 0.08774285 

boosting 43 : -0.4632635 
boosting mean 43 : -0.4643444 
boosting RMSE 43 : 0.1587736 

forest 43 : -0.3085663 
forest mean 43 : -0.4232288 
forest RMSE 43 : 0.06423283 

nnet 43 : -0.1320100 
nnet mean 43 : -0.3912841 
nnet RMSE 43 : 0.1413363 


s: 44 
logit 44 : -0.4843158 
logit mean 44 : -0.4670823 
logit RMSE 44 : 0.08766645 

boosting 44 : -0.4715886 
boosting mean 44 : -0.4645091 
boosting RMSE 44 : 0.1573296 

forest 44 : -0.4714809 
forest mean 44 : -0.4243255 
forest RMSE 44 : 0.06440662 

nnet 44 : -0.5399615 
nnet mean 44 : -0.3946631 
nnet RMSE 44 : 0.1413052 


s: 45 
logit 45 : -0.3864684 
logit mean 45 : -0.4652908 
logit RMSE 45 : 0.08671038 

boosting 45 : -0.338597 
boosting mean 45 : -0.461711 
boosting RMSE 45 : 0.1558408 

forest 45 : -0.3973728 
forest mean 45 : -0.4237265 
forest RMSE 45 : 0.06368818 

nnet 45 : -0.2957211 
nnet mean 45 : -0.3924644 
nnet RMSE 45 : 0.1405884 


s: 46 
logit 46 : -0.5117076 
logit mean 46 : -0.4662999 
logit RMSE 46 : 0.0873299 

boosting 46 : -0.4497452 
boosting mean 46 : -0.4614509 
boosting RMSE 46 : 0.1543119 

forest 46 : -0.4318107 
forest mean 46 : -0.4239023 
forest RMSE 46 : 0.06316648 

nnet 46 : -0.6178866 
nnet mean 46 : -0.3973649 
nnet RMSE 46 : 0.1427147 


s: 47 
logit 47 : -0.4658443 
logit mean 47 : -0.4662902 
logit RMSE 47 : 0.08692808 

boosting 47 : -0.6668176 
boosting mean 47 : -0.4658204 
boosting RMSE 47 : 0.1575444 

forest 47 : -0.3403053 
forest mean 47 : -0.4221236 
forest RMSE 47 : 0.0630946 

nnet 47 : -0.6469551 
nnet mean 47 : -0.4026753 
nnet RMSE 47 : 0.1457111 


s: 48 
logit 48 : -0.4502689 
logit mean 48 : -0.4659564 
logit RMSE 48 : 0.08632328 

boosting 48 : -0.3991268 
boosting mean 48 : -0.464431 
boosting RMSE 48 : 0.1558947 

forest 48 : -0.4715315 
forest mean 48 : -0.4231529 
forest RMSE 48 : 0.06328184 

nnet 48 : -0.4110527 
nnet mean 48 : -0.4028498 
nnet RMSE 48 : 0.1441941 


s: 49 
logit 49 : -0.4753656 
logit mean 49 : -0.4661485 
logit RMSE 49 : 0.0861136 

boosting 49 : -0.4409194 
boosting mean 49 : -0.4639511 
boosting RMSE 49 : 0.1544065 

forest 49 : -0.3590534 
forest mean 49 : -0.4218448 
forest RMSE 49 : 0.06290534 

nnet 49 : -0.2696408 
nnet mean 49 : -0.4001313 
nnet RMSE 49 : 0.1439250 


s: 50 
logit 50 : -0.4026141 
logit mean 50 : -0.4648778 
logit RMSE 50 : 0.08524891 

boosting 50 : -0.436365 
boosting mean 50 : -0.4633994 
boosting RMSE 50 : 0.1529411 

forest 50 : -0.4310894 
forest mean 50 : -0.4220297 
forest RMSE 50 : 0.06242813 

nnet 50 : -0.1480528 
nnet mean 50 : -0.3950897 
nnet RMSE 50 : 0.1468662 


s: 51 
logit 51 : -0.49045 
logit mean 51 : -0.4653792 
logit RMSE 51 : 0.08535394 

boosting 51 : -0.6348802 
boosting mean 51 : -0.4667618 
boosting RMSE 51 : 0.1549648 

forest 51 : -0.3522804 
forest mean 51 : -0.4206621 
forest RMSE 51 : 0.06217318 

nnet 51 : -0.5194693 
nnet mean 51 : -0.3975285 
nnet RMSE 51 : 0.1463783 


s: 52 
logit 52 : -0.4593116 
logit mean 52 : -0.4652625 
logit RMSE 52 : 0.08492846 

boosting 52 : -0.6173481 
boosting mean 52 : -0.4696577 
boosting RMSE 52 : 0.1563993 

forest 52 : -0.2996786 
forest mean 52 : -0.4183354 
forest RMSE 52 : 0.06312459 

nnet 52 : -0.4416787 
nnet mean 52 : -0.3983776 
nnet RMSE 52 : 0.1450791 


s: 53 
logit 53 : -0.4532494 
logit mean 53 : -0.4650358 
logit RMSE 53 : 0.08444082 

boosting 53 : -0.4899453 
boosting mean 53 : -0.4700405 
boosting RMSE 53 : 0.1554087 

forest 53 : -0.4579902 
forest mean 53 : -0.4190837 
forest RMSE 53 : 0.06303158 

nnet 53 : -0.3936761 
nnet mean 53 : -0.3982889 
nnet RMSE 53 : 0.1437066 


s: 54 
logit 54 : -0.4859113 
logit mean 54 : -0.4654224 
logit RMSE 54 : 0.08446829 

boosting 54 : -0.5137765 
boosting mean 54 : -0.4708504 
boosting RMSE 54 : 0.1547395 

forest 54 : -0.3395974 
forest mean 54 : -0.4176117 
forest RMSE 54 : 0.0629839 

nnet 54 : -0.158659 
nnet mean 54 : -0.3938513 
nnet RMSE 54 : 0.1461087 


s: 55 
logit 55 : -0.4578363 
logit mean 55 : -0.4652845 
logit RMSE 55 : 0.08405941 

boosting 55 : -0.2467532 
boosting mean 55 : -0.4667759 
boosting RMSE 55 : 0.1547125 

forest 55 : -0.3964036 
forest mean 55 : -0.4172261 
forest RMSE 55 : 0.06241057 

nnet 55 : -0.4141749 
nnet mean 55 : -0.3942208 
nnet RMSE 55 : 0.144787 


s: 56 
logit 56 : -0.3245014 
logit mean 56 : -0.4627705 
logit RMSE 56 : 0.0839142 

boosting 56 : -0.4469928 
boosting mean 56 : -0.4664226 
boosting RMSE 56 : 0.1534535 

forest 56 : -0.3861179 
forest mean 56 : -0.4166706 
forest RMSE 56 : 0.06187864 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 56 : -0.2057892 
nnet mean 56 : -0.3908559 
nnet RMSE 56 : 0.1458165 


s: 57 
logit 57 : -0.4785699 
logit mean 57 : -0.4630477 
logit RMSE 57 : 0.08382338 

boosting 57 : -0.3097291 
boosting mean 57 : -0.4636736 
boosting RMSE 57 : 0.1525707 

forest 57 : -0.3999295 
forest mean 57 : -0.4163769 
forest RMSE 57 : 0.06133344 

nnet 57 : -0.3185453 
nnet mean 57 : -0.3895873 
nnet RMSE 57 : 0.1449339 


s: 58 
logit 58 : -0.5035884 
logit mean 58 : -0.4637467 
logit RMSE 58 : 0.08420347 

boosting 58 : -0.2200388 
boosting mean 58 : -0.459473 
boosting RMSE 58 : 0.1530844 

forest 58 : -0.3353121 
forest mean 58 : -0.4149792 
forest RMSE 58 : 0.06139283 

nnet 58 : -0.2939401 
nnet mean 58 : -0.3879382 
nnet RMSE 58 : 0.1443524 


s: 59 
logit 59 : -0.6058357 
logit mean 59 : -0.466155 
logit RMSE 59 : 0.08768214 

boosting 59 : -0.3259523 
boosting mean 59 : -0.4572099 
boosting RMSE 59 : 0.1520874 

forest 59 : -0.4306896 
forest mean 59 : -0.4152455 
forest RMSE 59 : 0.06100132 

nnet 59 : -0.4506356 
nnet mean 59 : -0.3890009 
nnet RMSE 59 : 0.1432756 


s: 60 
logit 60 : -0.458021 
logit mean 60 : -0.4660194 
logit RMSE 60 : 0.08727044 

boosting 60 : -0.3370799 
boosting mean 60 : -0.4552078 
boosting RMSE 60 : 0.1510333 

forest 60 : -0.3846025 
forest mean 60 : -0.4147348 
forest RMSE 60 : 0.06052349 

nnet 60 : -0.4605407 
nnet mean 60 : -0.3901932 
nnet RMSE 60 : 0.1422914 


s: 61 
logit 61 : -0.4954364 
logit mean 61 : -0.4665016 
logit RMSE 61 : 0.08741046 

boosting 61 : -0.5042843 
boosting mean 61 : -0.4560123 
boosting RMSE 61 : 0.1503841 

forest 61 : -0.4033143 
forest mean 61 : -0.4145475 
forest RMSE 61 : 0.06002684 

nnet 61 : -0.4258525 
nnet mean 61 : -0.3907778 
nnet RMSE 61 : 0.1411591 


s: 62 
logit 62 : -0.3562523 
logit mean 62 : -0.4647234 
logit RMSE 62 : 0.0868805 

boosting 62 : -0.5333622 
boosting mean 62 : -0.4572599 
boosting RMSE 62 : 0.1501249 

forest 62 : -0.3608538 
forest mean 62 : -0.4136815 
forest RMSE 62 : 0.05974799 

nnet 62 : -0.4645229 
nnet mean 62 : -0.3919673 
nnet RMSE 62 : 0.1402557 


s: 63 
logit 63 : -0.4984175 
logit mean 63 : -0.4652582 
logit RMSE 63 : 0.08707557 

boosting 63 : -0.3095404 
boosting mean 63 : -0.4549151 
boosting RMSE 63 : 0.1493641 

forest 63 : -0.4224822 
forest mean 63 : -0.4138212 
forest RMSE 63 : 0.05933954 

nnet 63 : -0.3211501 
nnet mean 63 : -0.3908432 
nnet RMSE 63 : 0.1394923 


s: 64 
logit 64 : -0.3752703 
logit mean 64 : -0.4638522 
logit RMSE 64 : 0.0864479 

boosting 64 : -0.4509333 
boosting mean 64 : -0.4548529 
boosting RMSE 64 : 0.1483293 

forest 64 : -0.3407041 
forest mean 64 : -0.4126788 
forest RMSE 64 : 0.05933886 

nnet 64 : -0.330208 
nnet mean 64 : -0.3898958 
nnet RMSE 64 : 0.1386729 


s: 65 
logit 65 : -0.5434645 
logit mean 65 : -0.465077 
logit RMSE 65 : 0.08760658 

boosting 65 : -0.662123 
boosting mean 65 : -0.4580417 
boosting RMSE 65 : 0.1507320 

forest 65 : -0.427208 
forest mean 65 : -0.4129023 
forest RMSE 65 : 0.05897727 

nnet 65 : -0.3348349 
nnet mean 65 : -0.3890487 
nnet RMSE 65 : 0.1378392 


s: 66 
logit 66 : -0.4762139 
logit mean 66 : -0.4652457 
logit RMSE 66 : 0.08744504 

boosting 66 : -0.5887698 
boosting mean 66 : -0.4600224 
boosting RMSE 66 : 0.1513797 

forest 66 : -0.465634 
forest mean 66 : -0.4137013 
forest RMSE 66 : 0.05908372 

nnet 66 : -0.7215801 
nnet mean 66 : -0.394087 
nnet RMSE 66 : 0.1424031 


s: 67 
logit 67 : -0.5151826 
logit mean 67 : -0.4659911 
logit RMSE 67 : 0.08792339 

boosting 67 : -0.3596495 
boosting mean 67 : -0.4585243 
boosting RMSE 67 : 0.1503266 

forest 67 : -0.3645312 
forest mean 67 : -0.4129674 
forest RMSE 67 : 0.05880102 

nnet 67 : -0.3133088 
nnet mean 67 : -0.3928814 
nnet RMSE 67 : 0.1417327 


s: 68 
logit 68 : -0.5431624 
logit mean 68 : -0.4671259 
logit RMSE 68 : 0.0889845 

boosting 68 : -0.4441205 
boosting mean 68 : -0.4583125 
boosting RMSE 68 : 0.1493130 

forest 68 : -0.3612382 
forest mean 68 : -0.4122066 
forest RMSE 68 : 0.05855603 

nnet 68 : -0.6687312 
nnet mean 68 : -0.396938 
nnet RMSE 68 : 0.1444117 


s: 69 
logit 69 : -0.4581478 
logit mean 69 : -0.4669958 
logit RMSE 69 : 0.08861426 

boosting 69 : -0.4759566 
boosting mean 69 : -0.4585682 
boosting RMSE 69 : 0.1485089 

forest 69 : -0.4085062 
forest mean 69 : -0.412153 
forest RMSE 69 : 0.05813919 

nnet 69 : -0.1591333 
nnet mean 69 : -0.3934915 
nnet RMSE 69 : 0.1462646 


s: 70 
logit 70 : -0.6115134 
logit mean 70 : -0.4690603 
logit RMSE 70 : 0.09153918 

boosting 70 : -0.1688973 
boosting mean 70 : -0.4544301 
boosting RMSE 70 : 0.1500093 

forest 70 : -0.4818939 
forest mean 70 : -0.4131493 
forest RMSE 70 : 0.05854644 

nnet 70 : -0.6395085 
nnet mean 70 : -0.3970061 
nnet RMSE 70 : 0.1480108 


s: 71 
logit 71 : -0.4708291 
logit mean 71 : -0.4690853 
logit RMSE 71 : 0.09128012 

boosting 71 : -0.2681320 
boosting mean 71 : -0.4518061 
boosting RMSE 71 : 0.1497691 

forest 71 : -0.3846853 
forest mean 71 : -0.4127484 
forest RMSE 71 : 0.05816108 

nnet 71 : -0.421591 
nnet mean 71 : -0.3973523 
nnet RMSE 71 : 0.1469871 


s: 72 
logit 72 : -0.3756701 
logit mean 72 : -0.4677878 
logit RMSE 72 : 0.09068935 

boosting 72 : -0.3233315 
boosting mean 72 : -0.4500218 
boosting RMSE 72 : 0.1489996 

forest 72 : -0.3332013 
forest mean 72 : -0.4116436 
forest RMSE 72 : 0.05828982 

nnet 72 : -0.4790964 
nnet mean 72 : -0.3984877 
nnet RMSE 72 : 0.1462601 


s: 73 
logit 73 : -0.4199725 
logit mean 73 : -0.4671328 
logit RMSE 73 : 0.09009638 

boosting 73 : -0.4540462 
boosting mean 73 : -0.4500769 
boosting RMSE 73 : 0.1481107 

forest 73 : -0.4012542 
forest mean 73 : -0.4115013 
forest RMSE 73 : 0.05788938 

nnet 73 : -0.582268 
nnet mean 73 : -0.4010052 
nnet RMSE 73 : 0.1468131 


s: 74 
logit 74 : -0.4298679 
logit mean 74 : -0.4666292 
logit RMSE 74 : 0.08955289 

boosting 74 : -0.5123967 
boosting mean 74 : -0.4509191 
boosting RMSE 74 : 0.1476856 

forest 74 : -0.4176605 
forest mean 74 : -0.4115845 
forest RMSE 74 : 0.05753355 

nnet 74 : -0.3863472 
nnet mean 74 : -0.4008071 
nnet RMSE 74 : 0.1458264 


s: 75 
logit 75 : -0.5301782 
logit mean 75 : -0.4674766 
logit RMSE 75 : 0.09021497 

boosting 75 : -0.1962140 
boosting mean 75 : -0.447523 
boosting RMSE 75 : 0.1485730 

forest 75 : -0.3472697 
forest mean 75 : -0.410727 
forest RMSE 75 : 0.05747214 

nnet 75 : -0.3994722 
nnet mean 75 : -0.4007893 
nnet RMSE 75 : 0.1448509 


s: 76 
logit 76 : -0.490614 
logit mean 76 : -0.467781 
logit RMSE 76 : 0.09022023 

boosting 76 : -0.3601269 
boosting mean 76 : -0.446373 
boosting RMSE 76 : 0.1476632 

forest 76 : -0.3890329 
forest mean 76 : -0.4104415 
forest RMSE 76 : 0.05710664 

nnet 76 : -0.6002687 
nnet mean 76 : -0.4034141 
nnet RMSE 76 : 0.145717 


s: 77 
logit 77 : -0.5183382 
logit mean 77 : -0.4684376 
logit RMSE 77 : 0.09064132 

boosting 77 : -0.3467066 
boosting mean 77 : -0.4450787 
boosting RMSE 77 : 0.1468269 

forest 77 : -0.3430248 
forest mean 77 : -0.409566 
forest RMSE 77 : 0.05710494 

nnet 77 : -0.5338001 
nnet mean 77 : -0.4051074 
nnet RMSE 77 : 0.1455685 


s: 78 
logit 78 : -0.3922999 
logit mean 78 : -0.4674615 
logit RMSE 78 : 0.09006264 

boosting 78 : -0.828989 
boosting mean 78 : -0.4500006 
boosting RMSE 78 : 0.1537567 

forest 78 : -0.4766684 
forest mean 78 : -0.4104263 
forest RMSE 78 : 0.05739796 

nnet 78 : -0.8445008 
nnet mean 78 : -0.4107406 
nnet RMSE 78 : 0.1531392 


s: 79 
logit 79 : -0.4964986 
logit mean 79 : -0.467829 
logit RMSE 79 : 0.09014697 

boosting 79 : -0.6671769 
boosting mean 79 : -0.4527497 
boosting RMSE 79 : 0.1557095 

forest 79 : -0.464739 
forest mean 79 : -0.4111138 
forest RMSE 79 : 0.05749675 

nnet 79 : -0.4120478 
nnet mean 79 : -0.4107572 
nnet RMSE 79 : 0.1521729 


s: 80 
logit 80 : -0.4706853 
logit mean 80 : -0.4678647 
logit RMSE 80 : 0.0899297 

boosting 80 : -0.5678651 
boosting mean 80 : -0.4541886 
boosting RMSE 80 : 0.1558673 

forest 80 : -0.39677 
forest mean 80 : -0.4109345 
forest RMSE 80 : 0.0571374 

nnet 80 : -0.2982637 
nnet mean 80 : -0.409351 
nnet RMSE 80 : 0.151646 


s: 81 
logit 81 : -0.5267238 
logit mean 81 : -0.4685914 
logit RMSE 81 : 0.09047522 

boosting 81 : -0.5549684 
boosting mean 81 : -0.4554328 
boosting RMSE 81 : 0.1558563 

forest 81 : -0.2858564 
forest mean 81 : -0.4093903 
forest RMSE 81 : 0.0581827 

nnet 81 : -0.4314596 
nnet mean 81 : -0.4096240 
nnet RMSE 81 : 0.1507475 


s: 82 
logit 82 : -0.6022578 
logit mean 82 : -0.4702215 
logit RMSE 82 : 0.0926543 

boosting 82 : -0.6210513 
boosting mean 82 : -0.4574525 
boosting RMSE 82 : 0.1568147 

forest 82 : -0.5392094 
forest mean 82 : -0.4109735 
forest RMSE 82 : 0.05983541 

nnet 82 : -0.5815805 
nnet mean 82 : -0.411721 
nnet RMSE 82 : 0.1511614 


s: 83 
logit 83 : -0.4716359 
logit mean 83 : -0.4702385 
logit RMSE 83 : 0.09242952 

boosting 83 : -0.4303333 
boosting mean 83 : -0.4571258 
boosting RMSE 83 : 0.1559027 

forest 83 : -0.4830856 
forest mean 83 : -0.4118423 
forest RMSE 83 : 0.06016902 

nnet 83 : -0.2524451 
nnet mean 83 : -0.409802 
nnet RMSE 83 : 0.1511185 


s: 84 
logit 84 : -0.4559166 
logit mean 84 : -0.470068 
logit RMSE 84 : 0.09208004 

boosting 84 : -0.380493 
boosting mean 84 : -0.4562135 
boosting RMSE 84 : 0.1549865 

forest 84 : -0.4552854 
forest mean 84 : -0.4123595 
forest RMSE 84 : 0.06011322 

nnet 84 : -0.4095377 
nnet mean 84 : -0.4097989 
nnet RMSE 84 : 0.1502199 


s: 85 
logit 85 : -0.4357432 
logit mean 85 : -0.4696642 
logit RMSE 85 : 0.09161885 

boosting 85 : -0.6298854 
boosting mean 85 : -0.4582567 
boosting RMSE 85 : 0.1560768 

forest 85 : -0.4735202 
forest mean 85 : -0.413079 
forest RMSE 85 : 0.06028828 

nnet 85 : -0.3398771 
nnet mean 85 : -0.4089762 
nnet RMSE 85 : 0.1494760 


s: 86 
logit 86 : -0.4763966 
logit mean 86 : -0.4697425 
logit RMSE 86 : 0.0914564 

boosting 86 : -0.3762927 
boosting mean 86 : -0.4573036 
boosting RMSE 86 : 0.1551878 

forest 86 : -0.4273306 
forest mean 86 : -0.4132447 
forest RMSE 86 : 0.06000916 

nnet 86 : -0.5137723 
nnet mean 86 : -0.4101948 
nnet RMSE 86 : 0.1491099 


s: 87 
logit 87 : -0.5217991 
logit mean 87 : -0.4703408 
logit RMSE 87 : 0.09186213 

boosting 87 : -0.1792506 
boosting mean 87 : -0.4541076 
boosting RMSE 87 : 0.1560979 

forest 87 : -0.2495601 
forest mean 87 : -0.4113633 
forest RMSE 87 : 0.06180491 

nnet 87 : -0.2673113 
nnet mean 87 : -0.4085525 
nnet RMSE 87 : 0.1489315 


s: 88 
logit 88 : -0.4892292 
logit mean 88 : -0.4705555 
logit RMSE 88 : 0.09183263 

boosting 88 : -0.3922735 
boosting mean 88 : -0.453405 
boosting RMSE 88 : 0.1552106 

forest 88 : -0.4422369 
forest mean 88 : -0.4117141 
forest RMSE 88 : 0.06161746 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 88 : -0.2528358 
nnet mean 88 : -0.406783 
nnet RMSE 88 : 0.1489115 


s: 89 
logit 89 : -0.4937979 
logit mean 89 : -0.4708166 
logit RMSE 89 : 0.09185495 

boosting 89 : -0.6278076 
boosting mean 89 : -0.4553645 
boosting RMSE 89 : 0.1562138 

forest 89 : -0.4426124 
forest mean 89 : -0.4120613 
forest RMSE 89 : 0.06143659 

nnet 89 : -0.634266 
nnet mean 89 : -0.4093389 
nnet RMSE 89 : 0.1501403 


s: 90 
logit 90 : -0.4856937 
logit mean 90 : -0.4709819 
logit RMSE 90 : 0.09178876 

boosting 90 : -0.4087521 
boosting mean 90 : -0.4548466 
boosting RMSE 90 : 0.1553463 

forest 90 : -0.3911331 
forest mean 90 : -0.4118288 
forest RMSE 90 : 0.06110147 

nnet 90 : -0.5404995 
nnet mean 90 : -0.4107963 
nnet RMSE 90 : 0.1500366 


s: 91 
logit 91 : -0.5396835 
logit mean 91 : -0.4717369 
logit RMSE 91 : 0.09245001 

boosting 91 : -0.3113632 
boosting mean 91 : -0.4532699 
boosting RMSE 91 : 0.1547695 

forest 91 : -0.2942448 
forest mean 91 : -0.4105366 
forest RMSE 91 : 0.06176784 

nnet 91 : -0.1788527 
nnet mean 91 : -0.4082475 
nnet RMSE 91 : 0.1510001 


s: 92 
logit 92 : -0.5030908 
logit mean 92 : -0.4720777 
logit RMSE 92 : 0.09257225 

boosting 92 : -0.3464564 
boosting mean 92 : -0.4521089 
boosting RMSE 92 : 0.1540273 

forest 92 : -0.5928577 
forest mean 92 : -0.4125184 
forest RMSE 92 : 0.06463807 

nnet 92 : 0.005251775 
nnet mean 92 : -0.4037529 
nnet RMSE 92 : 0.1560074 


s: 93 
logit 93 : -0.5554903 
logit mean 93 : -0.4729746 
logit RMSE 93 : 0.0934743 

boosting 93 : -0.7594457 
boosting mean 93 : -0.4554136 
boosting RMSE 93 : 0.1576660 

forest 93 : -0.4076403 
forest mean 93 : -0.4124659 
forest RMSE 93 : 0.06429449 

nnet 93 : -0.5347565 
nnet mean 93 : -0.4051615 
nnet RMSE 93 : 0.1557943 


s: 94 
logit 94 : -0.4063998 
logit mean 94 : -0.4722663 
logit RMSE 94 : 0.0929781 

boosting 94 : -0.5236713 
boosting mean 94 : -0.4561397 
boosting RMSE 94 : 0.157343 

forest 94 : -0.4837691 
forest mean 94 : -0.4132245 
forest RMSE 94 : 0.0645326 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 94 : -0.307644 
nnet mean 94 : -0.4041241 
nnet RMSE 94 : 0.1552559 


s: 95 
logit 95 : -0.4984702 
logit mean 95 : -0.4725422 
logit RMSE 95 : 0.0930376 

boosting 95 : -0.5675677 
boosting mean 95 : -0.4573126 
boosting RMSE 95 : 0.1574541 

forest 95 : -0.5182057 
forest mean 95 : -0.4143295 
forest RMSE 95 : 0.06532764 

nnet 95 : -0.5094705 
nnet mean 95 : -0.405233 
nnet RMSE 95 : 0.1548445 


s: 96 
logit 96 : -0.3678151 
logit mean 96 : -0.4714513 
logit RMSE 96 : 0.09261004 

boosting 96 : -0.266988 
boosting mean 96 : -0.4553301 
boosting RMSE 96 : 0.1572191 

forest 96 : -0.3898392 
forest mean 96 : -0.4140744 
forest RMSE 96 : 0.06499477 

nnet 96 : -0.3713387 
nnet mean 96 : -0.40488 
nnet RMSE 96 : 0.1540636 


s: 97 
logit 97 : -0.4528156 
logit mean 97 : -0.4712591 
logit RMSE 97 : 0.09228737 

boosting 97 : -0.5525988 
boosting mean 97 : -0.4563329 
boosting RMSE 97 : 0.1571721 

forest 97 : -0.3981019 
forest mean 97 : -0.4139098 
forest RMSE 97 : 0.06465917 

nnet 97 : -0.5836066 
nnet mean 97 : -0.4067225 
nnet RMSE 97 : 0.1543970 


s: 98 
logit 98 : -0.4999973 
logit mean 98 : -0.4715524 
logit RMSE 98 : 0.0923693 

boosting 98 : -0.5148033 
boosting mean 98 : -0.4569295 
boosting RMSE 98 : 0.1567976 

forest 98 : -0.437094 
forest mean 98 : -0.4141463 
forest RMSE 98 : 0.06443747 

nnet 98 : -0.5646635 
nnet mean 98 : -0.4083342 
nnet RMSE 98 : 0.1545052 


s: 99 
logit 99 : -0.3894872 
logit mean 99 : -0.4707235 
logit RMSE 99 : 0.09190767 

boosting 99 : -0.2657494 
boosting mean 99 : -0.4549984 
boosting RMSE 99 : 0.1565861 

forest 99 : -0.3561978 
forest mean 99 : -0.413561 
forest RMSE 99 : 0.06426217 

nnet 99 : -0.3002101 
nnet mean 99 : -0.407242 
nnet RMSE 99 : 0.1540498 


s: 100 
logit 100 : -0.5100849 
logit mean 100 : -0.4711171 
logit RMSE 100 : 0.0921072 

boosting 100 : -0.4181463 
boosting mean 100 : -0.4546299 
boosting RMSE 100 : 0.1558118 

forest 100 : -0.4100949 
forest mean 100 : -0.4135263 
forest RMSE 100 : 0.06394802 

nnet 100 : -0.2113479 
nnet mean 100 : -0.4052830 
nnet RMSE 100 : 0.1544342 


s: 101 
logit 101 : -0.5868867 
logit mean 101 : -0.4722633 
logit RMSE 101 : 0.09351763 

boosting 101 : -0.5532348 
boosting mean 101 : -0.4556062 
boosting RMSE 101 : 0.1557865 

forest 101 : -0.6702888 
forest mean 101 : -0.4160685 
forest RMSE 101 : 0.06908102 

nnet 101 : -0.6207224 
nnet mean 101 : -0.4074161 
nnet RMSE 101 : 0.1552293 


s: 102 
logit 102 : -0.4693396 
logit mean 102 : -0.4722346 
logit RMSE 102 : 0.093311 

boosting 102 : 0.04789483 
boosting mean 102 : -0.4506699 
boosting RMSE 102 : 0.1612397 

forest 102 : -0.4215919 
forest mean 102 : -0.4161227 
forest RMSE 102 : 0.06877479 

nnet 102 : -0.2452099 
nnet mean 102 : -0.4058259 
nnet RMSE 102 : 0.155225 


s: 103 
logit 103 : -0.5196273 
logit mean 103 : -0.4726948 
logit RMSE 103 : 0.09360208 

boosting 103 : -0.4739462 
boosting mean 103 : -0.4508959 
boosting RMSE 103 : 0.1606204 

forest 103 : -0.414368 
forest mean 103 : -0.4161057 
forest RMSE 103 : 0.06845476 

nnet 103 : -0.2939173 
nnet mean 103 : -0.4047394 
nnet RMSE 103 : 0.1548229 


s: 104 
logit 104 : -0.4372955 
logit mean 104 : -0.4723544 
logit RMSE 104 : 0.09322274 

boosting 104 : -0.3363824 
boosting mean 104 : -0.4497948 
boosting RMSE 104 : 0.1599680 

forest 104 : -0.3921014 
forest mean 104 : -0.4158748 
forest RMSE 104 : 0.06812926 

nnet 104 : -0.6804575 
nnet mean 104 : -0.4073905 
nnet RMSE 104 : 0.1565118 


s: 105 
logit 105 : -0.4654366 
logit mean 105 : -0.4722885 
logit RMSE 105 : 0.09299728 

boosting 105 : -0.2505612 
boosting mean 105 : -0.4478973 
boosting RMSE 105 : 0.1598710 

forest 105 : -0.3730657 
forest mean 105 : -0.4154671 
forest RMSE 105 : 0.06785499 

nnet 105 : -0.2650383 
nnet mean 105 : -0.4060348 
nnet RMSE 105 : 0.1563206 


s: 106 
logit 106 : -0.4707371 
logit mean 106 : -0.4722739 
logit RMSE 106 : 0.09281223 

boosting 106 : -0.6087811 
boosting mean 106 : -0.4494151 
boosting RMSE 106 : 0.1604021 

forest 106 : -0.4569981 
forest mean 106 : -0.4158589 
forest RMSE 106 : 0.06776069 

nnet 106 : -0.3689396 
nnet mean 106 : -0.4056848 
nnet RMSE 106 : 0.1556107 


s: 107 
logit 107 : -0.5548916 
logit mean 107 : -0.473046 
logit RMSE 107 : 0.09358324 

boosting 107 : -0.6284886 
boosting mean 107 : -0.4510887 
boosting RMSE 107 : 0.1611717 

forest 107 : -0.4134971 
forest mean 107 : -0.4158369 
forest RMSE 107 : 0.06745593 

nnet 107 : -0.3765181 
nnet mean 107 : -0.4054122 
nnet RMSE 107 : 0.1548985 


s: 108 
logit 108 : -0.4720716 
logit mean 108 : -0.473037 
logit RMSE 108 : 0.09340678 

boosting 108 : -0.5514613 
boosting mean 108 : -0.452018 
boosting RMSE 108 : 0.1610844 

forest 108 : -0.4208322 
forest mean 108 : -0.4158831 
forest RMSE 108 : 0.06717282 

nnet 108 : -0.3498139 
nnet mean 108 : -0.4048974 
nnet RMSE 108 : 0.1542553 


s: 109 
logit 109 : -0.5336197 
logit mean 109 : -0.4735928 
logit RMSE 109 : 0.09385405 

boosting 109 : -0.2071317 
boosting mean 109 : -0.4497714 
boosting RMSE 109 : 0.1614045 

forest 109 : -0.3381745 
forest mean 109 : -0.4151702 
forest RMSE 109 : 0.0671257 

nnet 109 : -0.2597383 
nnet mean 109 : -0.4035657 
nnet RMSE 109 : 0.1541327 


s: 110 
logit 110 : -0.4301026 
logit mean 110 : -0.4731974 
logit RMSE 110 : 0.09347055 

boosting 110 : -0.5447494 
boosting mean 110 : -0.4506348 
boosting RMSE 110 : 0.1612608 

forest 110 : -0.4682461 
forest mean 110 : -0.4156527 
forest RMSE 110 : 0.06713597 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 110 : -0.2528846 
nnet mean 110 : -0.4021959 
nnet RMSE 110 : 0.1540704 


s: 111 
logit 111 : -0.5631155 
logit mean 111 : -0.4740075 
logit RMSE 111 : 0.0943278 

boosting 111 : -0.2481675 
boosting mean 111 : -0.4488108 
boosting RMSE 111 : 0.1611784 

forest 111 : -0.4450731 
forest mean 111 : -0.4159178 
forest RMSE 111 : 0.06696966 

nnet 111 : -0.3730951 
nnet mean 111 : -0.4019337 
nnet RMSE 111 : 0.1533961 


s: 112 
logit 112 : -0.4641498 
logit mean 112 : -0.4739195 
logit RMSE 112 : 0.09410118 

boosting 112 : -0.3661376 
boosting mean 112 : -0.4480726 
boosting RMSE 112 : 0.1604891 

forest 112 : -0.38245 
forest mean 112 : -0.4156189 
forest RMSE 112 : 0.06669064 

nnet 112 : -0.1589533 
nnet mean 112 : -0.3997642 
nnet RMSE 112 : 0.1543990 


s: 113 
logit 113 : -0.4093291 
logit mean 113 : -0.4733479 
logit RMSE 113 : 0.09368799 

boosting 113 : -0.2768517 
boosting mean 113 : -0.4465574 
boosting RMSE 113 : 0.1601968 

forest 113 : -0.420828 
forest mean 113 : -0.415665 
forest RMSE 113 : 0.0664238 

nnet 113 : -0.2309984 
nnet mean 113 : -0.3982707 
nnet RMSE 113 : 0.1545342 


s: 114 
logit 114 : -0.4794254 
logit mean 114 : -0.4734012 
logit RMSE 114 : 0.09357233 

boosting 114 : -0.3935909 
boosting mean 114 : -0.4460928 
boosting RMSE 114 : 0.1594938 

forest 114 : -0.3362775 
forest mean 114 : -0.4149687 
forest RMSE 114 : 0.06640058 

nnet 114 : -0.318835 
nnet mean 114 : -0.3975739 
nnet RMSE 114 : 0.1540426 


s: 115 
logit 115 : -0.4439695 
logit mean 115 : -0.4731453 
logit RMSE 115 : 0.09325479 

boosting 115 : -0.5327876 
boosting mean 115 : -0.4468466 
boosting RMSE 115 : 0.1592809 

forest 115 : -0.4093498 
forest mean 115 : -0.4149198 
forest RMSE 115 : 0.066117 

nnet 115 : -0.3663559 
nnet mean 115 : -0.3973025 
nnet RMSE 115 : 0.1534035 


s: 116 
logit 116 : -0.4945539 
logit mean 116 : -0.4733298 
logit RMSE 116 : 0.09326606 

boosting 116 : -0.490336 
boosting mean 116 : -0.4472215 
boosting RMSE 116 : 0.1588145 

forest 116 : -0.4251703 
forest mean 116 : -0.4150082 
forest RMSE 116 : 0.06587286 

nnet 116 : -0.3574492 
nnet mean 116 : -0.3969589 
nnet RMSE 116 : 0.1527920 


s: 117 
logit 117 : -0.4205405 
logit mean 117 : -0.4728786 
logit RMSE 117 : 0.09288605 

boosting 117 : -0.4227039 
boosting mean 117 : -0.447012 
boosting RMSE 117 : 0.1581482 

forest 117 : -0.4658294 
forest mean 117 : -0.4154425 
forest RMSE 117 : 0.06587249 

nnet 117 : -0.4399273 
nnet mean 117 : -0.3973261 
nnet RMSE 117 : 0.1521824 


s: 118 
logit 118 : -0.4849363 
logit mean 118 : -0.4729808 
logit RMSE 118 : 0.09282154 

boosting 118 : -0.4790332 
boosting mean 118 : -0.4472834 
boosting RMSE 118 : 0.1576447 

forest 118 : -0.5074086 
forest mean 118 : -0.4162219 
forest RMSE 118 : 0.06633386 

nnet 118 : -0.561522 
nnet mean 118 : -0.3987176 
nnet RMSE 118 : 0.1522639 


s: 119 
logit 119 : -0.3703051 
logit mean 119 : -0.472118 
logit RMSE 119 : 0.09247078 

boosting 119 : -0.4747002 
boosting mean 119 : -0.4475138 
boosting RMSE 119 : 0.1571302 

forest 119 : -0.4501423 
forest mean 119 : -0.4165069 
forest RMSE 119 : 0.06621429 

nnet 119 : -0.2725590 
nnet mean 119 : -0.3976575 
nnet RMSE 119 : 0.1520722 


s: 120 
logit 120 : -0.4343782 
logit mean 120 : -0.4718035 
logit RMSE 120 : 0.09213814 

boosting 120 : -0.5381763 
boosting mean 120 : -0.4482693 
boosting RMSE 120 : 0.1569817 

forest 120 : -0.4719859 
forest mean 120 : -0.4169693 
forest RMSE 120 : 0.06626446 

nnet 120 : -0.1074623 
nnet mean 120 : -0.3952392 
nnet RMSE 120 : 0.1537738 


s: 121 
logit 121 : -0.4428599 
logit mean 121 : -0.4715643 
logit RMSE 121 : 0.0918393 

boosting 121 : -0.5482831 
boosting mean 121 : -0.4490958 
boosting RMSE 121 : 0.1569118 

forest 121 : -0.5247147 
forest mean 121 : -0.4178597 
forest RMSE 121 : 0.06695695 

nnet 121 : -0.5319051 
nnet mean 121 : -0.3963687 
nnet RMSE 121 : 0.1536059 


s: 122 
logit 122 : -0.4670247 
logit mean 122 : -0.4715271 
logit RMSE 122 : 0.09166322 

boosting 122 : -0.328662 
boosting mean 122 : -0.4481087 
boosting RMSE 122 : 0.1564008 

forest 122 : -0.3659352 
forest mean 122 : -0.4174341 
forest RMSE 122 : 0.06675326 

nnet 122 : -0.3740216 
nnet mean 122 : -0.3961855 
nnet RMSE 122 : 0.1529931 


s: 123 
logit 123 : -0.3658445 
logit mean 123 : -0.4706679 
logit RMSE 123 : 0.09134178 

boosting 123 : -0.6206705 
boosting mean 123 : -0.4495116 
boosting RMSE 123 : 0.1570294 

forest 123 : -0.3246656 
forest mean 123 : -0.4166799 
forest RMSE 123 : 0.06682747 

nnet 123 : -0.3799543 
nnet mean 123 : -0.3960535 
nnet RMSE 123 : 0.1523806 


s: 124 
logit 124 : -0.4607579 
logit mean 124 : -0.4705879 
logit RMSE 124 : 0.0911362 

boosting 124 : -0.5132604 
boosting mean 124 : -0.4500257 
boosting RMSE 124 : 0.1567253 

forest 124 : -0.489586 
forest mean 124 : -0.4172679 
forest RMSE 124 : 0.06704191 

nnet 124 : -0.3358295 
nnet mean 124 : -0.3955678 
nnet RMSE 124 : 0.1518743 


s: 125 
logit 125 : -0.4570426 
logit mean 125 : -0.4704796 
logit RMSE 125 : 0.09091419 

boosting 125 : -0.481556 
boosting mean 125 : -0.450278 
boosting RMSE 125 : 0.1562675 

forest 125 : -0.3647490 
forest mean 125 : -0.4168477 
forest RMSE 125 : 0.0668476 

nnet 125 : -0.4168016 
nnet mean 125 : -0.3957377 
nnet RMSE 125 : 0.1512731 


s: 126 
logit 126 : -0.4993545 
logit mean 126 : -0.4707087 
logit RMSE 126 : 0.09098426 

boosting 126 : -0.5486704 
boosting mean 126 : -0.4510589 
boosting RMSE 126 : 0.1562087 

forest 126 : -0.3770361 
forest mean 126 : -0.4165317 
forest RMSE 126 : 0.06661323 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 126 : -0.2968150 
nnet mean 126 : -0.3949526 
nnet RMSE 126 : 0.1509517 


s: 127 
logit 127 : -0.362212 
logit mean 127 : -0.4698544 
logit RMSE 127 : 0.09068736 

boosting 127 : -0.4480563 
boosting mean 127 : -0.4510352 
boosting RMSE 127 : 0.1556509 

forest 127 : -0.4412197 
forest mean 127 : -0.4167261 
forest RMSE 127 : 0.06645119 

nnet 127 : -0.3109912 
nnet mean 127 : -0.3942915 
nnet RMSE 127 : 0.1505636 


s: 128 
logit 128 : -0.3742626 
logit mean 128 : -0.4691076 
logit RMSE 128 : 0.09036106 

boosting 128 : -0.60623 
boosting mean 128 : -0.4522477 
boosting RMSE 128 : 0.1561096 

forest 128 : -0.3656637 
forest mean 128 : -0.4163272 
forest RMSE 128 : 0.06626065 

nnet 128 : -0.6028132 
nnet mean 128 : -0.3959206 
nnet RMSE 128 : 0.1510418 


s: 129 
logit 129 : -0.4872316 
logit mean 129 : -0.4692481 
logit RMSE 129 : 0.09033721 

boosting 129 : -0.302264 
boosting mean 129 : -0.451085 
boosting RMSE 129 : 0.1557412 

forest 129 : -0.4559032 
forest mean 129 : -0.416634 
forest RMSE 129 : 0.06618659 

nnet 129 : -0.2087019 
nnet mean 129 : -0.3944693 
nnet RMSE 129 : 0.1513951 


s: 130 
logit 130 : -0.4853995 
logit mean 130 : -0.4693724 
logit RMSE 130 : 0.09030026 

boosting 130 : -0.3452688 
boosting mean 130 : -0.450271 
boosting RMSE 130 : 0.1552153 

forest 130 : -0.4882368 
forest mean 130 : -0.4171848 
forest RMSE 130 : 0.06638417 

nnet 130 : -0.3200653 
nnet mean 130 : -0.3938969 
nnet RMSE 130 : 0.1509745 


s: 131 
logit 131 : -0.550702 
logit mean 131 : -0.4699932 
logit RMSE 131 : 0.09091347 

boosting 131 : -0.4967874 
boosting mean 131 : -0.4506261 
boosting RMSE 131 : 0.1548528 

forest 131 : -0.5237656 
forest mean 131 : -0.4179984 
forest RMSE 131 : 0.06700857 

nnet 131 : -0.1863919 
nnet mean 131 : -0.3923129 
nnet RMSE 131 : 0.1515507 


s: 132 
logit 132 : -0.500839 
logit mean 132 : -0.4702269 
logit RMSE 132 : 0.09099273 

boosting 132 : -0.500778 
boosting mean 132 : -0.4510061 
boosting RMSE 132 : 0.1545143 

forest 132 : -0.3593224 
forest mean 132 : -0.4175539 
forest RMSE 132 : 0.06684809 

nnet 132 : -0.476992 
nnet mean 132 : -0.3929544 
nnet RMSE 132 : 0.1511242 


s: 133 
logit 133 : -0.3877755 
logit mean 133 : -0.4696069 
logit RMSE 133 : 0.0906562 

boosting 133 : -0.4413909 
boosting mean 133 : -0.4509338 
boosting RMSE 133 : 0.1539742 

forest 133 : -0.3918191 
forest mean 133 : -0.4173604 
forest RMSE 133 : 0.06660009 

nnet 133 : -0.1850702 
nnet mean 133 : -0.3913914 
nnet RMSE 133 : 0.1517041 


s: 134 
logit 134 : -0.4102240 
logit mean 134 : -0.4691638 
logit RMSE 134 : 0.09032162 

boosting 134 : -0.4426231 
boosting mean 134 : -0.4508717 
boosting RMSE 134 : 0.1534428 

forest 134 : -0.4034659 
forest mean 134 : -0.4172567 
forest RMSE 134 : 0.06635179 

nnet 134 : -0.3754331 
nnet mean 134 : -0.3912723 
nnet RMSE 134 : 0.1511519 


s: 135 
logit 135 : -0.5266442 
logit mean 135 : -0.4695896 
logit RMSE 135 : 0.0906442 

boosting 135 : -0.423102 
boosting mean 135 : -0.4506660 
boosting RMSE 135 : 0.1528863 

forest 135 : -0.4583073 
forest mean 135 : -0.4175608 
forest RMSE 135 : 0.06629579 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 135 : -0.2644543 
nnet mean 135 : -0.3903329 
nnet RMSE 135 : 0.1510422 


s: 136 
logit 136 : -0.4263198 
logit mean 136 : -0.4692714 
logit RMSE 136 : 0.09033853 

boosting 136 : -0.5113244 
boosting mean 136 : -0.4511121 
boosting RMSE 136 : 0.1526220 

forest 136 : -0.3802975 
forest mean 136 : -0.4172868 
forest RMSE 136 : 0.06607321 

nnet 136 : -0.4257206 
nnet mean 136 : -0.3905931 
nnet RMSE 136 : 0.1505021 


s: 137 
logit 137 : -0.505082 
logit mean 137 : -0.4695328 
logit RMSE 137 : 0.09045486 

boosting 137 : -0.4452199 
boosting mean 137 : -0.4510691 
boosting RMSE 137 : 0.1521131 

forest 137 : -0.4037157 
forest mean 137 : -0.4171877 
forest RMSE 137 : 0.06583239 

nnet 137 : -0.4829241 
nnet mean 137 : -0.3912671 
nnet RMSE 137 : 0.1501191 


s: 138 
logit 138 : -0.4258116 
logit mean 138 : -0.469216 
logit RMSE 138 : 0.0901533 

boosting 138 : -0.8072395 
boosting mean 138 : -0.45365 
boosting RMSE 138 : 0.1554750 

forest 138 : -0.4236905 
forest mean 138 : -0.4172348 
forest RMSE 138 : 0.06562443 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 138 : -0.2017724 
nnet mean 138 : -0.3898939 
nnet RMSE 138 : 0.150523 


s: 139 
logit 139 : -0.4861577 
logit mean 139 : -0.4693379 
logit RMSE 139 : 0.0901252 

boosting 139 : -0.4683343 
boosting mean 139 : -0.4537556 
boosting RMSE 139 : 0.1550231 

forest 139 : -0.3423816 
forest mean 139 : -0.4166963 
forest RMSE 139 : 0.06557032 

nnet 139 : -0.3050514 
nnet mean 139 : -0.3892835 
nnet RMSE 139 : 0.1501966 


s: 140 
logit 140 : -0.5494404 
logit mean 140 : -0.46991 
logit RMSE 140 : 0.09068655 

boosting 140 : -0.5772429 
boosting mean 140 : -0.4546377 
boosting RMSE 140 : 0.1551931 

forest 140 : -0.452043 
forest mean 140 : -0.4169488 
forest RMSE 140 : 0.0654836 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 140 : -0.266811 
nnet mean 140 : -0.3884087 
nnet RMSE 140 : 0.150082 


s: 141 
logit 141 : -0.5052977 
logit mean 141 : -0.470161 
logit RMSE 141 : 0.09079845 

boosting 141 : -0.6470375 
boosting mean 141 : -0.4560022 
boosting RMSE 141 : 0.1560350 

forest 141 : -0.3704466 
forest mean 141 : -0.416619 
forest RMSE 141 : 0.06529843 

nnet 141 : -0.3275262 
nnet mean 141 : -0.3879769 
nnet RMSE 141 : 0.1496733 


s: 142 
logit 142 : -0.4455111 
logit mean 142 : -0.4699874 
logit RMSE 142 : 0.09055874 

boosting 142 : -0.4398341 
boosting mean 142 : -0.4558884 
boosting RMSE 142 : 0.1555205 

forest 142 : -0.4972552 
forest mean 142 : -0.4171869 
forest RMSE 142 : 0.06557795 

nnet 142 : -0.4149236 
nnet mean 142 : -0.3881667 
nnet RMSE 142 : 0.1491506 


s: 143 
logit 143 : -0.5162046 
logit mean 143 : -0.4703106 
logit RMSE 143 : 0.09076325 

boosting 143 : -0.5601599 
boosting mean 143 : -0.4566175 
boosting RMSE 143 : 0.1555534 

forest 143 : -0.4158308 
forest mean 143 : -0.4171774 
forest RMSE 143 : 0.06536166 

nnet 143 : -0.7840796 
nnet mean 143 : -0.3909353 
nnet RMSE 143 : 0.1520590 


s: 144 
logit 144 : -0.5734724 
logit mean 144 : -0.471027 
logit RMSE 144 : 0.0915955 

boosting 144 : -0.5339819 
boosting mean 144 : -0.4571548 
boosting RMSE 144 : 0.1554140 

forest 144 : -0.4107035 
forest mean 144 : -0.4171324 
forest RMSE 144 : 0.06514042 

nnet 144 : -0.6257546 
nnet mean 144 : -0.392566 
nnet RMSE 144 : 0.1526935 


s: 145 
logit 145 : -0.498683 
logit mean 145 : -0.4712177 
logit RMSE 145 : 0.09164626 

boosting 145 : -0.7069934 
boosting mean 145 : -0.4588778 
boosting RMSE 145 : 0.1569614 

forest 145 : -0.4121819 
forest mean 145 : -0.4170983 
forest RMSE 145 : 0.06492329 

nnet 145 : -0.5381264 
nnet mean 145 : -0.3935699 
nnet RMSE 145 : 0.1525978 


s: 146 
logit 146 : -0.4754775 
logit mean 146 : -0.4712469 
logit RMSE 146 : 0.09154523 

boosting 146 : -0.2916027 
boosting mean 146 : -0.4577321 
boosting RMSE 146 : 0.15668 

forest 146 : -0.3143046 
forest mean 146 : -0.4163942 
forest RMSE 146 : 0.06508812 

nnet 146 : -0.2723625 
nnet mean 146 : -0.3927397 
nnet RMSE 146 : 0.1524407 


s: 147 
logit 147 : -0.4549425 
logit mean 147 : -0.471136 
logit RMSE 147 : 0.09134579 

boosting 147 : -0.3138492 
boosting mean 147 : -0.4567533 
boosting RMSE 147 : 0.1563078 

forest 147 : -0.4226195 
forest mean 147 : -0.4164366 
forest RMSE 147 : 0.06489318 

nnet 147 : -0.5986934 
nnet mean 147 : -0.3941407 
nnet RMSE 147 : 0.1528026 


s: 148 
logit 148 : -0.4853944 
logit mean 148 : -0.4712323 
logit RMSE 148 : 0.09130688 

boosting 148 : -0.3812808 
boosting mean 148 : -0.4562434 
boosting RMSE 148 : 0.1557864 

forest 148 : -0.3322095 
forest mean 148 : -0.4158674 
forest RMSE 148 : 0.06491319 

nnet 148 : -0.4763635 
nnet mean 148 : -0.3946963 
nnet RMSE 148 : 0.1524149 


s: 149 
logit 149 : -0.4654061 
logit mean 149 : -0.4711932 
logit RMSE 149 : 0.09115758 

boosting 149 : -0.4555453 
boosting mean 149 : -0.4562387 
boosting RMSE 149 : 0.1553294 

forest 149 : -0.347412 
forest mean 149 : -0.415408 
forest RMSE 149 : 0.06483828 

nnet 149 : -0.4807774 
nnet mean 149 : -0.395274 
nnet RMSE 149 : 0.1520466 


s: 150 
logit 150 : -0.4634412 
logit mean 150 : -0.4711416 
logit RMSE 150 : 0.09100076 

boosting 150 : -0.3222615 
boosting mean 150 : -0.4553455 
boosting RMSE 150 : 0.1549408 

forest 150 : -0.4278330 
forest mean 150 : -0.4154909 
forest RMSE 150 : 0.06466173 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 150 : -0.2531587 
nnet mean 150 : -0.3943266 
nnet RMSE 150 : 0.1520125 


s: 151 
logit 151 : -0.4427419 
logit mean 151 : -0.4709535 
logit RMSE 151 : 0.0907656 

boosting 151 : -0.8116644 
boosting mean 151 : -0.4577052 
boosting RMSE 151 : 0.1580189 

forest 151 : -0.4351588 
forest mean 151 : -0.4156211 
forest RMSE 151 : 0.06451075 

nnet 151 : -0.5200458 
nnet mean 151 : -0.3951592 
nnet RMSE 151 : 0.1518229 


s: 152 
logit 152 : -0.4523408 
logit mean 152 : -0.470831 
logit RMSE 152 : 0.0905661 

boosting 152 : -0.4880724 
boosting mean 152 : -0.457905 
boosting RMSE 152 : 0.1576602 

forest 152 : -0.4364582 
forest mean 152 : -0.4157582 
forest RMSE 152 : 0.06436616 

nnet 152 : -0.3242823 
nnet mean 152 : -0.3946929 
nnet RMSE 152 : 0.1514473 


s: 153 
logit 153 : -0.5525924 
logit mean 153 : -0.4713654 
logit RMSE 153 : 0.0911087 

boosting 153 : -0.5710153 
boosting mean 153 : -0.4586443 
boosting RMSE 153 : 0.1577512 

forest 153 : -0.3996176 
forest mean 153 : -0.4156527 
forest RMSE 153 : 0.06415547 

nnet 153 : -0.3856182 
nnet mean 153 : -0.3946336 
nnet RMSE 153 : 0.150956 


s: 154 
logit 154 : -0.4432461 
logit mean 154 : -0.4711828 
logit RMSE 154 : 0.09087925 

boosting 154 : -0.3889813 
boosting mean 154 : -0.4581919 
boosting RMSE 154 : 0.1572406 

forest 154 : -0.3665203 
forest mean 154 : -0.4153337 
forest RMSE 154 : 0.06400372 

nnet 154 : -0.258691 
nnet mean 154 : -0.3937508 
nnet RMSE 154 : 0.1508954 


s: 155 
logit 155 : -0.438157 
logit mean 155 : -0.4709698 
logit RMSE 155 : 0.09063745 

boosting 155 : -0.4263997 
boosting mean 155 : -0.4579868 
boosting RMSE 155 : 0.1567469 

forest 155 : -0.4094354 
forest mean 155 : -0.4152956 
forest RMSE 155 : 0.06380143 

nnet 155 : -0.5224988 
nnet mean 155 : -0.3945814 
nnet RMSE 155 : 0.1507293 


s: 156 
logit 156 : -0.4582316 
logit mean 156 : -0.4708881 
logit RMSE 156 : 0.0904667 

boosting 156 : -0.3405707 
boosting mean 156 : -0.4572341 
boosting RMSE 156 : 0.1563162 

forest 156 : -0.4454893 
forest mean 156 : -0.4154891 
forest RMSE 156 : 0.0637008 

nnet 156 : -0.6215303 
nnet mean 156 : -0.3960362 
nnet RMSE 156 : 0.1512887 


s: 157 
logit 157 : -0.4917898 
logit mean 157 : -0.4710212 
logit RMSE 157 : 0.09047518 

boosting 157 : -0.5424596 
boosting mean 157 : -0.457777 
boosting RMSE 157 : 0.1562318 

forest 157 : -0.4277494 
forest mean 157 : -0.4155672 
forest RMSE 157 : 0.06353622 

nnet 157 : -0.1577425 
nnet mean 157 : -0.3945185 
nnet RMSE 157 : 0.1520405 


s: 158 
logit 158 : -0.5220149 
logit mean 158 : -0.471344 
logit RMSE 158 : 0.0907093 

boosting 158 : -0.4363769 
boosting mean 158 : -0.4576415 
boosting RMSE 158 : 0.1557635 

forest 158 : -0.4420453 
forest mean 158 : -0.4157348 
forest RMSE 158 : 0.06342311 

nnet 158 : -0.6274963 
nnet mean 158 : -0.395993 
nnet RMSE 158 : 0.1526354 


s: 159 
logit 159 : -0.53359 
logit mean 159 : -0.4717355 
logit RMSE 159 : 0.09104212 

boosting 159 : -0.4208263 
boosting mean 159 : -0.45741 
boosting RMSE 159 : 0.1552817 

forest 159 : -0.4382753 
forest mean 159 : -0.4158766 
forest RMSE 159 : 0.06329617 

nnet 159 : -0.5362247 
nnet mean 159 : -0.3968750 
nnet RMSE 159 : 0.1525377 


s: 160 
logit 160 : -0.6102366 
logit mean 160 : -0.4726011 
logit RMSE 160 : 0.09226651 

boosting 160 : -0.4230183 
boosting mean 160 : -0.4571951 
boosting RMSE 160 : 0.1548064 

forest 160 : -0.4576559 
forest mean 160 : -0.4161377 
forest RMSE 160 : 0.06326248 

nnet 160 : -0.2676163 
nnet mean 160 : -0.3960671 
nnet RMSE 160 : 0.15242 


s: 161 
logit 161 : -0.5066066 
logit mean 161 : -0.4728123 
logit RMSE 161 : 0.09236245 

boosting 161 : -0.3400048 
boosting mean 161 : -0.4564672 
boosting RMSE 161 : 0.1543973 

forest 161 : -0.4099083 
forest mean 161 : -0.416099 
forest RMSE 161 : 0.06307055 

nnet 161 : -0.02541499 
nnet mean 161 : -0.3937649 
nnet RMSE 161 : 0.1547872 


s: 162 
logit 162 : -0.4658678 
logit mean 162 : -0.4727694 
logit RMSE 162 : 0.09222226 

boosting 162 : -0.3896419 
boosting mean 162 : -0.4560547 
boosting RMSE 162 : 0.1539222 

forest 162 : -0.3455156 
forest mean 162 : -0.4156633 
forest RMSE 162 : 0.06302113 

nnet 162 : -0.4227073 
nnet mean 162 : -0.3939436 
nnet RMSE 162 : 0.1543190 


s: 163 
logit 163 : -0.5231944 
logit mean 163 : -0.4730788 
logit RMSE 163 : 0.0924439 

boosting 163 : -0.4049276 
boosting mean 163 : -0.455741 
boosting RMSE 163 : 0.1534498 

forest 163 : -0.4108432 
forest mean 163 : -0.4156337 
forest RMSE 163 : 0.06283326 

nnet 163 : -0.4705357 
nnet mean 163 : -0.3944134 
nnet RMSE 163 : 0.1539441 


s: 164 
logit 164 : -0.5460204 
logit mean 164 : -0.4735236 
logit RMSE 164 : 0.0928643 

boosting 164 : -0.5861589 
boosting mean 164 : -0.4565362 
boosting RMSE 164 : 0.1536703 

forest 164 : -0.4632683 
forest mean 164 : -0.4159242 
forest RMSE 164 : 0.06283592 

nnet 164 : -0.3557386 
nnet mean 164 : -0.3941776 
nnet RMSE 164 : 0.1535129 


s: 165 
logit 165 : -0.455274 
logit mean 165 : -0.473413 
logit RMSE 165 : 0.09268242 

boosting 165 : -0.578624 
boosting mean 165 : -0.4572762 
boosting RMSE 165 : 0.1538337 

forest 165 : -0.3586648 
forest mean 165 : -0.4155772 
forest RMSE 165 : 0.06272781 

nnet 165 : -0.5601704 
nnet mean 165 : -0.3951836 
nnet RMSE 165 : 0.1535542 


s: 166 
logit 166 : -0.4258113 
logit mean 166 : -0.4731262 
logit RMSE 166 : 0.09242455 

boosting 166 : -0.4523465 
boosting mean 166 : -0.4572465 
boosting RMSE 166 : 0.1534235 

forest 166 : -0.3326695 
forest mean 166 : -0.4150777 
forest RMSE 166 : 0.06275655 

nnet 166 : -0.3066278 
nnet mean 166 : -0.3946502 
nnet RMSE 166 : 0.1532624 


s: 167 
logit 167 : -0.4077978 
logit mean 167 : -0.472735 
logit RMSE 167 : 0.09214939 

boosting 167 : -0.5422745 
boosting mean 167 : -0.4577556 
boosting RMSE 167 : 0.1533591 

forest 167 : -0.3481018 
forest mean 167 : -0.4146767 
forest RMSE 167 : 0.06269713 

nnet 167 : -0.3622596 
nnet mean 167 : -0.3944562 
nnet RMSE 167 : 0.1528307 


s: 168 
logit 168 : -0.5447099 
logit mean 168 : -0.4731634 
logit RMSE 168 : 0.0925506 

boosting 168 : -0.3335585 
boosting mean 168 : -0.4570163 
boosting RMSE 168 : 0.1529879 

forest 168 : -0.3937577 
forest mean 168 : -0.4145522 
forest RMSE 168 : 0.06251211 

nnet 168 : -0.4937764 
nnet mean 168 : -0.3950474 
nnet RMSE 168 : 0.1525469 


s: 169 
logit 169 : -0.4897367 
logit mean 169 : -0.4732615 
logit RMSE 169 : 0.0925342 

boosting 169 : -0.5204756 
boosting mean 169 : -0.4573918 
boosting RMSE 169 : 0.1528159 

forest 169 : -0.51018 
forest mean 169 : -0.415118 
forest RMSE 169 : 0.0629005 

nnet 169 : -0.3427584 
nnet mean 169 : -0.394738 
nnet RMSE 169 : 0.1521586 


s: 170 
logit 170 : -0.5174175 
logit mean 170 : -0.4735212 
logit RMSE 170 : 0.0927001 

boosting 170 : -0.4239198 
boosting mean 170 : -0.4571949 
boosting RMSE 170 : 0.1523768 

forest 170 : -0.5097152 
forest mean 170 : -0.4156745 
forest RMSE 170 : 0.06327723 

nnet 170 : -0.3367818 
nnet mean 170 : -0.3943971 
nnet RMSE 170 : 0.1517879 


s: 171 
logit 171 : -0.5200089 
logit mean 171 : -0.4737931 
logit RMSE 171 : 0.09288315 

boosting 171 : -0.3557769 
boosting mean 171 : -0.4566019 
boosting RMSE 171 : 0.1519682 

forest 171 : -0.3397454 
forest mean 171 : -0.4152304 
forest RMSE 171 : 0.06325997 

nnet 171 : -0.4452935 
nnet mean 171 : -0.3946947 
nnet RMSE 171 : 0.1513830 


s: 172 
logit 172 : -0.504788 
logit mean 172 : -0.4739733 
logit RMSE 172 : 0.09295677 

boosting 172 : -0.429469 
boosting mean 172 : -0.4564441 
boosting RMSE 172 : 0.1515425 

forest 172 : -0.4162441 
forest mean 172 : -0.4152363 
forest RMSE 172 : 0.06308797 

nnet 172 : -0.2493792 
nnet mean 172 : -0.3938499 
nnet RMSE 172 : 0.1513786 


s: 173 
logit 173 : -0.418467 
logit mean 173 : -0.4736525 
logit RMSE 173 : 0.09269835 

boosting 173 : -0.4811865 
boosting mean 173 : -0.4565871 
boosting RMSE 173 : 0.1512299 

forest 173 : -0.2877006 
forest mean 173 : -0.4144991 
forest RMSE 173 : 0.06348214 

nnet 173 : -0.2854056 
nnet mean 173 : -0.393223 
nnet RMSE 173 : 0.1511917 


s: 174 
logit 174 : -0.4379711 
logit mean 174 : -0.4734474 
logit RMSE 174 : 0.0924764 

boosting 174 : -0.2580411 
boosting mean 174 : -0.4554461 
boosting RMSE 174 : 0.1511782 

forest 174 : -0.3741837 
forest mean 174 : -0.4142674 
forest RMSE 174 : 0.06332971 

nnet 174 : -0.1038976 
nnet mean 174 : -0.3915602 
nnet RMSE 174 : 0.1524187 


s: 175 
logit 175 : -0.4632697 
logit mean 175 : -0.4733892 
logit RMSE 175 : 0.09233576 

boosting 175 : -0.1404805 
boosting mean 175 : -0.4536463 
boosting RMSE 175 : 0.1520168 

forest 175 : -0.3969727 
forest mean 175 : -0.4141686 
forest RMSE 175 : 0.06314892 

nnet 175 : -0.1525008 
nnet mean 175 : -0.3901942 
nnet RMSE 175 : 0.1531298 


s: 176 
logit 176 : -0.4729637 
logit mean 176 : -0.4733868 
logit RMSE 176 : 0.09223718 

boosting 176 : -0.4441992 
boosting mean 176 : -0.4535926 
boosting RMSE 176 : 0.1516210 

forest 176 : -0.3924471 
forest mean 176 : -0.4140452 
forest RMSE 176 : 0.06297184 

nnet 176 : -0.2737039 
nnet mean 176 : -0.3895323 
nnet RMSE 176 : 0.1529906 


s: 177 
logit 177 : -0.479693 
logit mean 177 : -0.4734224 
logit RMSE 177 : 0.0921711 

boosting 177 : -0.5123393 
boosting mean 177 : -0.4539245 
boosting RMSE 177 : 0.1514277 

forest 177 : -0.4756617 
forest mean 177 : -0.4143933 
forest RMSE 177 : 0.06305071 

nnet 177 : -0.3022550 
nnet mean 177 : -0.3890392 
nnet RMSE 177 : 0.1527346 


s: 178 
logit 178 : -0.4380864 
logit mean 178 : -0.4732239 
logit RMSE 178 : 0.09195616 

boosting 178 : -0.7143425 
boosting mean 178 : -0.4553875 
boosting RMSE 178 : 0.1528288 

forest 178 : -0.4855844 
forest mean 178 : -0.4147932 
forest RMSE 178 : 0.06319975 

nnet 178 : -0.6201463 
nnet mean 178 : -0.3903376 
nnet RMSE 178 : 0.1531962 


s: 179 
logit 179 : -0.4299784 
logit mean 179 : -0.4729823 
logit RMSE 179 : 0.0917263 

boosting 179 : -0.5198665 
boosting mean 179 : -0.4557477 
boosting RMSE 179 : 0.1526644 

forest 179 : -0.4523622 
forest mean 179 : -0.4150031 
forest RMSE 179 : 0.06314437 

nnet 179 : -0.4072049 
nnet mean 179 : -0.3904318 
nnet RMSE 179 : 0.1527686 


s: 180 
logit 180 : -0.5838606 
logit mean 180 : -0.4735983 
logit RMSE 180 : 0.09249204 

boosting 180 : -0.2968525 
boosting mean 180 : -0.454865 
boosting RMSE 180 : 0.1524337 

forest 180 : -0.4847222 
forest mean 180 : -0.4153905 
forest RMSE 180 : 0.06328457 

nnet 180 : -0.5455121 
nnet mean 180 : -0.3912934 
nnet RMSE 180 : 0.1527293 


s: 181 
logit 181 : -0.5075607 
logit mean 181 : -0.473786 
logit RMSE 181 : 0.09258203 

boosting 181 : -0.794271 
boosting mean 181 : -0.4567401 
boosting RMSE 181 : 0.1548112 

forest 181 : -0.4385475 
forest mean 181 : -0.4155184 
forest RMSE 181 : 0.06317452 

nnet 181 : -0.4420132 
nnet mean 181 : -0.3915736 
nnet RMSE 181 : 0.1523388 


s: 182 
logit 182 : -0.4051761 
logit mean 182 : -0.473409 
logit RMSE 182 : 0.09232813 

boosting 182 : -0.4749471 
boosting mean 182 : -0.4568402 
boosting RMSE 182 : 0.1544852 

forest 182 : -0.4206049 
forest mean 182 : -0.4155463 
forest RMSE 182 : 0.06301924 

nnet 182 : -0.6312503 
nnet mean 182 : -0.3928905 
nnet RMSE 182 : 0.1528837 


s: 183 
logit 183 : -0.4982227 
logit mean 183 : -0.4735446 
logit RMSE 183 : 0.09236136 

boosting 183 : -0.511915 
boosting mean 183 : -0.4571411 
boosting RMSE 183 : 0.1542845 

forest 183 : -0.3280306 
forest mean 183 : -0.4150681 
forest RMSE 183 : 0.0630716 

nnet 183 : -0.06240251 
nnet mean 183 : -0.3910845 
nnet RMSE 183 : 0.1544943 


s: 184 
logit 184 : -0.4052006 
logit mean 184 : -0.4731731 
logit RMSE 184 : 0.09211083 

boosting 184 : -0.5403012 
boosting mean 184 : -0.4575931 
boosting RMSE 184 : 0.1542120 

forest 184 : -0.4128708 
forest mean 184 : -0.4150562 
forest RMSE 184 : 0.06290713 

nnet 184 : -0.4018252 
nnet mean 184 : -0.3911429 
nnet RMSE 184 : 0.154074 


s: 185 
logit 185 : -0.5448518 
logit mean 185 : -0.4735606 
logit RMSE 185 : 0.09247681 

boosting 185 : -0.5988478 
boosting mean 185 : -0.4583566 
boosting RMSE 185 : 0.1544879 

forest 185 : -0.4564933 
forest mean 185 : -0.4152802 
forest RMSE 185 : 0.06287422 

nnet 185 : -0.8860918 
nnet mean 185 : -0.3938183 
nnet RMSE 185 : 0.1577584 


s: 186 
logit 186 : -0.463628 
logit mean 186 : -0.4735072 
logit RMSE 186 : 0.0923458 

boosting 186 : -0.5837122 
boosting mean 186 : -0.4590306 
boosting RMSE 186 : 0.1546598 

forest 186 : -0.4487298 
forest mean 186 : -0.41546 
forest RMSE 186 : 0.06280669 

nnet 186 : -0.1627156 
nnet mean 186 : -0.3925758 
nnet RMSE 186 : 0.1582928 


s: 187 
logit 187 : -0.5322717 
logit mean 187 : -0.4738214 
logit RMSE 187 : 0.0926051 

boosting 187 : -0.4123558 
boosting mean 187 : -0.458781 
boosting RMSE 187 : 0.1542483 

forest 187 : -0.4211024 
forest mean 187 : -0.4154902 
forest RMSE 187 : 0.06265754 

nnet 187 : -0.4875998 
nnet mean 187 : -0.393084 
nnet RMSE 187 : 0.1579989 


s: 188 
logit 188 : -0.4598846 
logit mean 188 : -0.4737473 
logit RMSE 188 : 0.0924617 

boosting 188 : -0.4934874 
boosting mean 188 : -0.4589656 
boosting RMSE 188 : 0.1539886 

forest 188 : -0.3396979 
forest mean 188 : -0.415087 
forest RMSE 188 : 0.06264524 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 188 : -0.1574169 
nnet mean 188 : -0.3918304 
nnet RMSE 188 : 0.1585682 


s: 189 
logit 189 : -0.4166776 
logit mean 189 : -0.4734454 
logit RMSE 189 : 0.09222475 

boosting 189 : -0.4293724 
boosting mean 189 : -0.458809 
boosting RMSE 189 : 0.1535955 

forest 189 : -0.3566008 
forest mean 189 : -0.4147776 
forest RMSE 189 : 0.062559 

nnet 189 : -0.058919 
nnet mean 189 : -0.390069 
nnet RMSE 189 : 0.1600824 


s: 190 
logit 190 : -0.5311502 
logit mean 190 : -0.4737491 
logit RMSE 190 : 0.09247252 

boosting 190 : -0.5108585 
boosting mean 190 : -0.459083 
boosting RMSE 190 : 0.1534018 

forest 190 : -0.4725659 
forest mean 190 : -0.4150817 
forest RMSE 190 : 0.06261585 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 190 : -0.2309245 
nnet mean 190 : -0.3892314 
nnet RMSE 190 : 0.1601311 


s: 191 
logit 191 : -0.4838143 
logit mean 191 : -0.4738018 
logit RMSE 191 : 0.0924293 

boosting 191 : -0.3752817 
boosting mean 191 : -0.4586442 
boosting RMSE 191 : 0.1530101 

forest 191 : -0.4056895 
forest mean 191 : -0.4150325 
forest RMSE 191 : 0.06245308 

nnet 191 : -0.2796679 
nnet mean 191 : -0.3886578 
nnet RMSE 191 : 0.1599485 


s: 192 
logit 192 : -0.3879085 
logit mean 192 : -0.4733544 
logit RMSE 192 : 0.09219241 

boosting 192 : -0.5116979 
boosting mean 192 : -0.4589205 
boosting RMSE 192 : 0.1528239 

forest 192 : -0.3861963 
forest mean 192 : -0.4148824 
forest RMSE 192 : 0.06229819 

nnet 192 : -0.4309919 
nnet mean 192 : -0.3888782 
nnet RMSE 192 : 0.1595471 


s: 193 
logit 193 : -0.4608593 
logit mean 193 : -0.4732897 
logit RMSE 193 : 0.09205756 

boosting 193 : -0.4112318 
boosting mean 193 : -0.4586734 
boosting RMSE 193 : 0.1524296 

forest 193 : -0.4072687 
forest mean 193 : -0.4148429 
forest RMSE 193 : 0.06213879 

nnet 193 : -0.3889119 
nnet mean 193 : -0.3888784 
nnet RMSE 193 : 0.1591352 


s: 194 
logit 194 : -0.4699441 
logit mean 194 : -0.4732724 
logit RMSE 194 : 0.0919572 

boosting 194 : -0.5194837 
boosting mean 194 : -0.4589869 
boosting RMSE 194 : 0.1522781 

forest 194 : -0.3690120 
forest mean 194 : -0.4146067 
forest RMSE 194 : 0.06201835 

nnet 194 : -0.3740766 
nnet mean 194 : -0.3888021 
nnet RMSE 194 : 0.1587354 


s: 195 
logit 195 : -0.4234149 
logit mean 195 : -0.4730167 
logit RMSE 195 : 0.09173644 

boosting 195 : -0.4726814 
boosting mean 195 : -0.4590571 
boosting RMSE 195 : 0.1519763 

forest 195 : -0.3875086 
forest mean 195 : -0.4144677 
forest RMSE 195 : 0.06186559 

nnet 195 : -0.5049449 
nnet mean 195 : -0.3893977 
nnet RMSE 195 : 0.1585062 


s: 196 
logit 196 : -0.4737428 
logit mean 196 : -0.4730204 
logit RMSE 196 : 0.0916536 

boosting 196 : -0.3261707 
boosting mean 196 : -0.4583791 
boosting RMSE 196 : 0.1516798 

forest 196 : -0.3959431 
forest mean 196 : -0.4143732 
forest RMSE 196 : 0.06170825 

nnet 196 : -0.2521761 
nnet mean 196 : -0.3886976 
nnet RMSE 196 : 0.1584535 


s: 197 
logit 197 : -0.5140664 
logit mean 197 : -0.4732288 
logit RMSE 197 : 0.0917812 

boosting 197 : -0.7361089 
boosting mean 197 : -0.4597889 
boosting RMSE 197 : 0.1531777 

forest 197 : -0.4390072 
forest mean 197 : -0.4144982 
forest RMSE 197 : 0.06161414 

nnet 197 : -0.2261334 
nnet mean 197 : -0.3878724 
nnet RMSE 197 : 0.1585355 


s: 198 
logit 198 : -0.4050242 
logit mean 198 : -0.4728843 
logit RMSE 198 : 0.09154983 

boosting 198 : -0.3612842 
boosting mean 198 : -0.4592914 
boosting RMSE 198 : 0.1528152 

forest 198 : -0.4019561 
forest mean 198 : -0.4144349 
forest RMSE 198 : 0.06145851 

nnet 198 : -0.2085576 
nnet mean 198 : -0.3869668 
nnet RMSE 198 : 0.1587189 


s: 199 
logit 199 : -0.5191979 
logit mean 199 : -0.4731171 
logit RMSE 199 : 0.0917096 

boosting 199 : -0.4873473 
boosting mean 199 : -0.4594324 
boosting RMSE 199 : 0.1525565 

forest 199 : -0.390154 
forest mean 199 : -0.4143129 
forest RMSE 199 : 0.06130787 

nnet 199 : -0.4901497 
nnet mean 199 : -0.3874853 
nnet RMSE 199 : 0.1584485 


s: 200 
logit 200 : -0.4547066 
logit mean 200 : -0.473025 
logit RMSE 200 : 0.0915618 

boosting 200 : -0.3649234 
boosting mean 200 : -0.4589599 
boosting RMSE 200 : 0.1521948 

forest 200 : -0.4499015 
forest mean 200 : -0.4144908 
forest RMSE 200 : 0.06125612 

nnet 200 : -0.3628823 
nnet mean 200 : -0.3873623 
nnet RMSE 200 : 0.1580737 


s: 201 
logit 201 : -0.4322687 
logit mean 201 : -0.4728222 
logit RMSE 201 : 0.0913621 

boosting 201 : -0.1786837 
boosting mean 201 : -0.4575655 
boosting RMSE 201 : 0.1526162 

forest 201 : -0.3260143 
forest mean 201 : -0.4140506 
forest RMSE 201 : 0.06132599 

nnet 201 : -0.4271312 
nnet mean 201 : -0.3875601 
nnet RMSE 201 : 0.1576916 


s: 202 
logit 202 : -0.4229863 
logit mean 202 : -0.4725755 
logit RMSE 202 : 0.09115002 

boosting 202 : -0.2458185 
boosting mean 202 : -0.4565172 
boosting RMSE 202 : 0.1526240 

forest 202 : -0.3606725 
forest mean 202 : -0.4137864 
forest RMSE 202 : 0.06123656 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 202 : -0.2448319 
nnet mean 202 : -0.3868536 
nnet RMSE 202 : 0.1576792 


s: 203 
logit 203 : -0.4890177 
logit mean 203 : -0.4726565 
logit RMSE 203 : 0.09113964 

boosting 203 : -0.2261572 
boosting mean 203 : -0.4553824 
boosting RMSE 203 : 0.1527357 

forest 203 : -0.325498 
forest mean 203 : -0.4133515 
forest RMSE 203 : 0.06130894 

nnet 203 : -0.3354986 
nnet mean 203 : -0.3866006 
nnet RMSE 203 : 0.1573555 


s: 204 
logit 204 : -0.5777575 
logit mean 204 : -0.4731717 
logit RMSE 204 : 0.09176387 

boosting 204 : -0.5298563 
boosting mean 204 : -0.4557475 
boosting RMSE 204 : 0.1526319 

forest 204 : -0.4099191 
forest mean 204 : -0.4133346 
forest RMSE 204 : 0.06116243 

nnet 204 : -0.1901060 
nnet mean 204 : -0.3856374 
nnet RMSE 204 : 0.1576557 


s: 205 
logit 205 : -0.372044 
logit mean 205 : -0.4726784 
logit RMSE 205 : 0.0915606 

boosting 205 : -0.5717468 
boosting mean 205 : -0.4563133 
boosting RMSE 205 : 0.152731 

forest 205 : -0.5072082 
forest mean 205 : -0.4137926 
forest RMSE 205 : 0.06147082 

nnet 205 : -0.5203146 
nnet mean 205 : -0.3862943 
nnet RMSE 205 : 0.1574950 


s: 206 
logit 206 : -0.4986767 
logit mean 206 : -0.4728046 
logit RMSE 206 : 0.09159648 

boosting 206 : -0.7313847 
boosting mean 206 : -0.4576486 
boosting RMSE 206 : 0.1540993 

forest 206 : -0.4421038 
forest mean 206 : -0.41393 
forest RMSE 206 : 0.06139156 

nnet 206 : -0.3203526 
nnet mean 206 : -0.3859742 
nnet RMSE 206 : 0.1572103 


s: 207 
logit 207 : -0.5057382 
logit mean 207 : -0.4729637 
logit RMSE 207 : 0.09167004 

boosting 207 : -0.4846722 
boosting mean 207 : -0.4577792 
boosting RMSE 207 : 0.1538393 

forest 207 : -0.525031 
forest mean 207 : -0.4144667 
forest RMSE 207 : 0.06185658 

nnet 207 : -0.4169999 
nnet mean 207 : -0.3861241 
nnet RMSE 207 : 0.1568345 


s: 208 
logit 208 : -0.5220779 
logit mean 208 : -0.4731998 
logit RMSE 208 : 0.09184032 

boosting 208 : -0.4604526 
boosting mean 208 : -0.4577920 
boosting RMSE 208 : 0.1535263 

forest 208 : -0.4956164 
forest mean 208 : -0.4148569 
forest RMSE 208 : 0.06206284 

nnet 208 : -0.5770361 
nnet mean 208 : -0.3870420 
nnet RMSE 208 : 0.1569379 


s: 209 
logit 209 : -0.4541587 
logit mean 209 : -0.4731087 
logit RMSE 209 : 0.0916969 

boosting 209 : -0.3205325 
boosting mean 209 : -0.4571353 
boosting RMSE 209 : 0.1532571 

forest 209 : -0.4117970 
forest mean 209 : -0.4148422 
forest RMSE 209 : 0.06191956 

nnet 209 : -0.5899963 
nnet mean 209 : -0.388013 
nnet RMSE 209 : 0.1571126 


s: 210 
logit 210 : -0.5310374 
logit mean 210 : -0.4733846 
logit RMSE 210 : 0.09192414 

boosting 210 : -0.2150869 
boosting mean 210 : -0.4559827 
boosting RMSE 210 : 0.1534234 

forest 210 : -0.470249 
forest mean 210 : -0.4151061 
forest RMSE 210 : 0.06196188 

nnet 210 : -0.4638269 
nnet mean 210 : -0.3883740 
nnet RMSE 210 : 0.1568000 


s: 211 
logit 211 : -0.4969453 
logit mean 211 : -0.4734963 
logit RMSE 211 : 0.09194858 

boosting 211 : -0.2961249 
boosting mean 211 : -0.4552251 
boosting RMSE 211 : 0.1532263 

forest 211 : -0.3284826 
forest mean 211 : -0.4146955 
forest RMSE 211 : 0.06201064 

nnet 211 : -0.7086962 
nnet mean 211 : -0.3898922 
nnet RMSE 211 : 0.1578649 


s: 212 
logit 212 : -0.4889879 
logit mean 212 : -0.4735693 
logit RMSE 212 : 0.09193484 

boosting 212 : -0.211633 
boosting mean 212 : -0.4540761 
boosting RMSE 212 : 0.1534110 

forest 212 : -0.3990825 
forest mean 212 : -0.4146219 
forest RMSE 212 : 0.06186425 

nnet 212 : -0.2154919 
nnet mean 212 : -0.3890695 
nnet RMSE 212 : 0.1580011 


s: 213 
logit 213 : -0.5092873 
logit mean 213 : -0.473737 
logit RMSE 213 : 0.09202395 

boosting 213 : -0.5376522 
boosting mean 213 : -0.4544684 
boosting RMSE 213 : 0.1533408 

forest 213 : -0.5304642 
forest mean 213 : -0.4151657 
forest RMSE 213 : 0.06236287 

nnet 213 : -0.4306805 
nnet mean 213 : -0.3892649 
nnet RMSE 213 : 0.1576438 


s: 214 
logit 214 : -0.4620157 
logit mean 214 : -0.4736822 
logit RMSE 214 : 0.09190652 

boosting 214 : -0.5203874 
boosting mean 214 : -0.4547765 
boosting RMSE 214 : 0.1532033 

forest 214 : -0.5165549 
forest mean 214 : -0.4156395 
forest RMSE 214 : 0.06272508 

nnet 214 : -0.6459586 
nnet mean 214 : -0.3904644 
nnet RMSE 214 : 0.1581712 


s: 215 
logit 215 : -0.560213 
logit mean 215 : -0.4740847 
logit RMSE 215 : 0.09234126 

boosting 215 : -0.2577168 
boosting mean 215 : -0.4538599 
boosting RMSE 215 : 0.1531543 

forest 215 : -0.3775344 
forest mean 215 : -0.4154623 
forest RMSE 215 : 0.06259779 

nnet 215 : -0.1947173 
nnet mean 215 : -0.3895539 
nnet RMSE 215 : 0.1584228 


s: 216 
logit 216 : -0.3766860 
logit mean 216 : -0.4736338 
logit RMSE 216 : 0.09214091 

boosting 216 : -0.2942587 
boosting mean 216 : -0.453121 
boosting RMSE 216 : 0.1529686 

forest 216 : -0.4112431 
forest mean 216 : -0.4154427 
forest RMSE 216 : 0.0624574 

nnet 216 : -0.4923751 
nnet mean 216 : -0.3900299 
nnet RMSE 216 : 0.1581806 


s: 217 
logit 217 : -0.4404653 
logit mean 217 : -0.4734809 
logit RMSE 217 : 0.0919694 

boosting 217 : -0.746485 
boosting mean 217 : -0.4544729 
boosting RMSE 217 : 0.1544176 

forest 217 : -0.4268872 
forest mean 217 : -0.4154955 
forest RMSE 217 : 0.06234005 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 217 : -0.2586403 
nnet mean 217 : -0.3894245 
nnet RMSE 217 : 0.1581072 


s: 218 
logit 218 : -0.3377108 
logit mean 218 : -0.4728581 
logit RMSE 218 : 0.09185514 

boosting 218 : -0.4793302 
boosting mean 218 : -0.4545869 
boosting RMSE 218 : 0.1541567 

forest 218 : -0.4522869 
forest mean 218 : -0.4156643 
forest RMSE 218 : 0.06229764 

nnet 218 : -0.4404361 
nnet mean 218 : -0.3896585 
nnet RMSE 218 : 0.1577679 


s: 219 
logit 219 : -0.4525785 
logit mean 219 : -0.4727655 
logit RMSE 219 : 0.09171403 

boosting 219 : -0.3969623 
boosting mean 219 : -0.4543238 
boosting RMSE 219 : 0.1538045 

forest 219 : -0.3386876 
forest mean 219 : -0.4153128 
forest RMSE 219 : 0.06229318 

nnet 219 : -0.3046589 
nnet mean 219 : -0.3892703 
nnet RMSE 219 : 0.1575391 


s: 220 
logit 220 : -0.513056 
logit mean 220 : -0.4729487 
logit RMSE 220 : 0.09182226 

boosting 220 : -0.3737117 
boosting mean 220 : -0.4539574 
boosting RMSE 220 : 0.1534648 

forest 220 : -0.4262128 
forest mean 220 : -0.4153623 
forest RMSE 220 : 0.06217656 

nnet 220 : -0.4389277 
nnet mean 220 : -0.3894961 
nnet RMSE 220 : 0.1572025 


s: 221 
logit 221 : -0.4355229 
logit mean 221 : -0.4727793 
logit RMSE 221 : 0.09164544 

boosting 221 : -0.8565305 
boosting mean 221 : -0.455779 
boosting RMSE 221 : 0.1561664 

forest 221 : -0.418364 
forest mean 221 : -0.4153759 
forest RMSE 221 : 0.06204803 

nnet 221 : -0.518945 
nnet mean 221 : -0.3900818 
nnet RMSE 221 : 0.1570504 


s: 222 
logit 222 : -0.4430507 
logit mean 222 : -0.4726454 
logit RMSE 222 : 0.09148444 

boosting 222 : -0.7711243 
boosting mean 222 : -0.4571995 
boosting RMSE 222 : 0.1577926 

forest 222 : -0.4497514 
forest mean 222 : -0.4155307 
forest RMSE 222 : 0.0619981 

nnet 222 : -0.2356418 
nnet mean 222 : -0.3893861 
nnet RMSE 222 : 0.1570841 


s: 223 
logit 223 : -0.4346592 
logit mean 223 : -0.4724751 
logit RMSE 223 : 0.09130859 

boosting 223 : -0.4671845 
boosting mean 223 : -0.4572442 
boosting RMSE 223 : 0.1575027 

forest 223 : -0.4222226 
forest mean 223 : -0.4155607 
forest RMSE 223 : 0.06187684 

nnet 223 : -0.2419451 
nnet mean 223 : -0.3887249 
nnet RMSE 223 : 0.1570884 


s: 224 
logit 224 : -0.4759242 
logit mean 224 : -0.4724905 
logit RMSE 224 : 0.09124567 

boosting 224 : -0.2679505 
boosting mean 224 : -0.4563992 
boosting RMSE 224 : 0.1573982 

forest 224 : -0.3276782 
forest mean 224 : -0.4151684 
forest RMSE 224 : 0.06192738 

nnet 224 : -0.6019192 
nnet mean 224 : -0.3896767 
nnet RMSE 224 : 0.1573170 


s: 225 
logit 225 : -0.5049587 
logit mean 225 : -0.4726348 
logit RMSE 225 : 0.09131118 

boosting 225 : -0.428629 
boosting mean 225 : -0.4562758 
boosting RMSE 225 : 0.1570597 

forest 225 : -0.4414752 
forest mean 225 : -0.4152853 
forest RMSE 225 : 0.06185145 

nnet 225 : -0.4709215 
nnet mean 225 : -0.3900378 
nnet RMSE 225 : 0.1570382 


s: 226 
logit 226 : -0.4999893 
logit mean 226 : -0.4727558 
logit RMSE 226 : 0.0913514 

boosting 226 : -0.479537 
boosting mean 226 : -0.4563787 
boosting RMSE 226 : 0.1568011 

forest 226 : -0.4458455 
forest mean 226 : -0.4154206 
forest RMSE 226 : 0.06178976 

nnet 226 : -0.7322598 
nnet mean 226 : -0.3915521 
nnet RMSE 226 : 0.1582414 


s: 227 
logit 227 : -0.364408 
logit mean 227 : -0.4722785 
logit RMSE 227 : 0.09118056 

boosting 227 : -0.3044007 
boosting mean 227 : -0.4557092 
boosting RMSE 227 : 0.1565839 

forest 227 : -0.3621762 
forest mean 227 : -0.415186 
forest RMSE 227 : 0.0617046 

nnet 227 : -0.5688608 
nnet mean 227 : -0.3923331 
nnet RMSE 227 : 0.1582898 


s: 228 
logit 228 : -0.5429884 
logit mean 228 : -0.4725886 
logit RMSE 228 : 0.09147188 

boosting 228 : -0.3903399 
boosting mean 228 : -0.4554225 
boosting RMSE 228 : 0.1562415 

forest 228 : -0.3297264 
forest mean 228 : -0.4148112 
forest RMSE 228 : 0.06174478 

nnet 228 : -0.3424975 
nnet mean 228 : -0.3921146 
nnet RMSE 228 : 0.1579882 


s: 229 
logit 229 : -0.481818 
logit mean 229 : -0.4726289 
logit RMSE 229 : 0.09143194 

boosting 229 : -0.6164367 
boosting mean 229 : -0.4561256 
boosting RMSE 229 : 0.1565547 

forest 229 : -0.4859385 
forest mean 229 : -0.4151218 
forest RMSE 229 : 0.061871 

nnet 229 : -0.4539442 
nnet mean 229 : -0.3923846 
nnet RMSE 229 : 0.1576831 


s: 230 
logit 230 : -0.4880719 
logit mean 230 : -0.4726961 
logit RMSE 230 : 0.0914176 

boosting 230 : -0.7254123 
boosting mean 230 : -0.4572964 
boosting RMSE 230 : 0.1576807 

forest 230 : -0.4784733 
forest mean 230 : -0.4153972 
forest RMSE 230 : 0.06195281 

nnet 230 : -0.4360482 
nnet mean 230 : -0.3925744 
nnet RMSE 230 : 0.1573579 


s: 231 
logit 231 : -0.4367092 
logit mean 231 : -0.4725403 
logit RMSE 231 : 0.09125148 

boosting 231 : -0.4702043 
boosting mean 231 : -0.4573523 
boosting RMSE 231 : 0.1574068 

forest 231 : -0.4613106 
forest mean 231 : -0.415596 
forest RMSE 231 : 0.06195004 

nnet 231 : -0.3832036 
nnet mean 231 : -0.3925338 
nnet RMSE 231 : 0.1570209 


s: 232 
logit 232 : -0.4434402 
logit mean 232 : -0.4724149 
logit RMSE 232 : 0.09109926 

boosting 232 : -0.5250155 
boosting mean 232 : -0.4576439 
boosting RMSE 232 : 0.1572815 

forest 232 : -0.4186708 
forest mean 232 : -0.4156092 
forest RMSE 232 : 0.06182854 

nnet 232 : -0.2523647 
nnet mean 232 : -0.3919297 
nnet RMSE 232 : 0.1569816 


s: 233 
logit 233 : -0.4607492 
logit mean 233 : -0.4723648 
logit RMSE 233 : 0.09099063 

boosting 233 : -0.3914988 
boosting mean 233 : -0.4573600 
boosting RMSE 233 : 0.1569446 

forest 233 : -0.4061045 
forest mean 233 : -0.4155684 
forest RMSE 233 : 0.06169701 

nnet 233 : -0.4773598 
nnet mean 233 : -0.3922963 
nnet RMSE 233 : 0.1567263 


s: 234 
logit 234 : -0.4208625 
logit mean 234 : -0.4721447 
logit RMSE 234 : 0.09080624 

boosting 234 : -0.3802872 
boosting mean 234 : -0.4570307 
boosting RMSE 234 : 0.1566142 

forest 234 : -0.4137304 
forest mean 234 : -0.4155606 
forest RMSE 234 : 0.06157158 

nnet 234 : -0.3258651 
nnet mean 234 : -0.3920124 
nnet RMSE 234 : 0.1564662 


s: 235 
logit 235 : -0.4397807 
logit mean 235 : -0.472007 
logit RMSE 235 : 0.09064998 

boosting 235 : -0.6108695 
boosting mean 235 : -0.4576853 
boosting RMSE 235 : 0.1568849 

forest 235 : -0.4161143 
forest mean 235 : -0.4155629 
forest RMSE 235 : 0.06144943 

nnet 235 : -0.5016354 
nnet mean 235 : -0.3924789 
nnet RMSE 235 : 0.1562736 


s: 236 
logit 236 : -0.5093264 
logit mean 236 : -0.4721651 
logit RMSE 236 : 0.09073723 

boosting 236 : -0.6317688 
boosting mean 236 : -0.4584230 
boosting RMSE 236 : 0.1572774 

forest 236 : -0.4384885 
forest mean 236 : -0.4156601 
forest RMSE 236 : 0.06137027 

nnet 236 : -0.4777564 
nnet mean 236 : -0.3928403 
nnet RMSE 236 : 0.1560243 


s: 237 
logit 237 : -0.4659474 
logit mean 237 : -0.4721389 
logit RMSE 237 : 0.09064687 

boosting 237 : -0.320506 
boosting mean 237 : -0.457841 
boosting RMSE 237 : 0.1570302 

forest 237 : -0.3580428 
forest mean 237 : -0.415417 
forest RMSE 237 : 0.06130127 

nnet 237 : -0.3622520 
nnet mean 237 : -0.3927112 
nnet RMSE 237 : 0.1557141 


s: 238 
logit 238 : -0.4368176 
logit mean 238 : -0.4719905 
logit RMSE 238 : 0.09048772 

boosting 238 : -0.4400491 
boosting mean 238 : -0.4577663 
boosting RMSE 238 : 0.1567214 

forest 238 : -0.319757 
forest mean 238 : -0.415015 
forest RMSE 238 : 0.06139309 

nnet 238 : -0.4772071 
nnet mean 238 : -0.3930662 
nnet RMSE 238 : 0.1554672 


s: 239 
logit 239 : -0.4467707 
logit mean 239 : -0.471885 
logit RMSE 239 : 0.09034888 

boosting 239 : -0.5284257 
boosting mean 239 : -0.4580619 
boosting RMSE 239 : 0.1566137 

forest 239 : -0.4575338 
forest mean 239 : -0.4151929 
forest RMSE 239 : 0.06137744 

nnet 239 : -0.4288705 
nnet mean 239 : -0.393216 
nnet RMSE 239 : 0.1551528 


s: 240 
logit 240 : -0.4186883 
logit mean 240 : -0.4716633 
logit RMSE 240 : 0.09016852 

boosting 240 : -0.4389435 
boosting mean 240 : -0.4579823 
boosting RMSE 240 : 0.1563073 

forest 240 : -0.4078098 
forest mean 240 : -0.4151622 
forest RMSE 240 : 0.06125151 

nnet 240 : -0.7119479 
nnet mean 240 : -0.3945441 
nnet RMSE 240 : 0.1561332 


s: 241 
logit 241 : -0.4562942 
logit mean 241 : -0.4715995 
logit RMSE 241 : 0.0900543 

boosting 241 : -0.5527997 
boosting mean 241 : -0.4583757 
boosting RMSE 241 : 0.1562929 

forest 241 : -0.4364779 
forest mean 241 : -0.4152506 
forest RMSE 241 : 0.06116945 

nnet 241 : -0.6570258 
nnet mean 241 : -0.3956332 
nnet RMSE 241 : 0.1566861 


s: 242 
logit 242 : -0.4525783 
logit mean 242 : -0.4715209 
logit RMSE 242 : 0.08993158 

boosting 242 : -0.5512038 
boosting mean 242 : -0.4587593 
boosting RMSE 242 : 0.1562722 

forest 242 : -0.4619649 
forest mean 242 : -0.4154437 
forest RMSE 242 : 0.06117276 

nnet 242 : -0.6211932 
nnet mean 242 : -0.3965653 
nnet RMSE 242 : 0.1570072 


s: 243 
logit 243 : -0.4511997 
logit mean 243 : -0.4714373 
logit RMSE 243 : 0.08980642 

boosting 243 : -0.4917582 
boosting mean 243 : -0.4588951 
boosting RMSE 243 : 0.1560614 

forest 243 : -0.4159014 
forest mean 243 : -0.4154455 
forest RMSE 243 : 0.06105528 

nnet 243 : -0.6904095 
nnet mean 243 : -0.3977745 
nnet RMSE 243 : 0.1577874 


s: 244 
logit 244 : -0.4358317 
logit mean 244 : -0.4712914 
logit RMSE 244 : 0.08965156 

boosting 244 : -0.5044354 
boosting mean 244 : -0.4590817 
boosting RMSE 244 : 0.1558847 

forest 244 : -0.3868119 
forest mean 244 : -0.4153282 
forest RMSE 244 : 0.06093589 

nnet 244 : -0.4602204 
nnet mean 244 : -0.3980304 
nnet RMSE 244 : 0.1575110 


s: 245 
logit 245 : -0.4490984 
logit mean 245 : -0.4712008 
logit RMSE 245 : 0.08952338 

boosting 245 : -0.3794777 
boosting mean 245 : -0.4587568 
boosting RMSE 245 : 0.1555717 

forest 245 : -0.4400502 
forest mean 245 : -0.4154291 
forest RMSE 245 : 0.06086521 

nnet 245 : -0.4840632 
nnet mean 245 : -0.3983816 
nnet RMSE 245 : 0.1572809 


s: 246 
logit 246 : -0.4397754 
logit mean 246 : -0.4710731 
logit RMSE 246 : 0.08937722 

boosting 246 : -0.5577434 
boosting mean 246 : -0.4591592 
boosting RMSE 246 : 0.1555806 

forest 246 : -0.4386253 
forest mean 246 : -0.4155234 
forest RMSE 246 : 0.06079128 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 246 : -0.2417353 
nnet mean 246 : -0.3977448 
nnet RMSE 246 : 0.1572849 


s: 247 
logit 247 : -0.3970123 
logit mean 247 : -0.4707732 
logit RMSE 247 : 0.08919631 

boosting 247 : -0.4500647 
boosting mean 247 : -0.4591224 
boosting RMSE 247 : 0.1552981 

forest 247 : -0.4073944 
forest mean 247 : -0.4154905 
forest RMSE 247 : 0.06066992 

nnet 247 : -0.4046393 
nnet mean 247 : -0.3977727 
nnet RMSE 247 : 0.1569665 


s: 248 
logit 248 : -0.4539498 
logit mean 248 : -0.4707054 
logit RMSE 248 : 0.0890822 

boosting 248 : -0.5525543 
boosting mean 248 : -0.4594991 
boosting RMSE 248 : 0.1552871 

forest 248 : -0.4150372 
forest mean 248 : -0.4154887 
forest RMSE 248 : 0.060555 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 248 : -0.2463513 
nnet mean 248 : -0.3971622 
nnet RMSE 248 : 0.1569532 


s: 249 
logit 249 : -0.4908303 
logit mean 249 : -0.4707862 
logit RMSE 249 : 0.08908929 

boosting 249 : -0.2858690 
boosting mean 249 : -0.4588018 
boosting RMSE 249 : 0.1551436 

forest 249 : -0.49783 
forest mean 249 : -0.4158193 
forest RMSE 249 : 0.06075046 

nnet 249 : -0.2027652 
nnet mean 249 : -0.3963814 
nnet RMSE 249 : 0.1571357 


s: 250 
logit 250 : -0.5110869 
logit mean 250 : -0.4709474 
logit RMSE 250 : 0.08918808 

boosting 250 : -0.3423112 
boosting mean 250 : -0.4583358 
boosting RMSE 250 : 0.1548760 

forest 250 : -0.3916705 
forest mean 250 : -0.4157227 
forest RMSE 250 : 0.06063113 

nnet 250 : -0.5018711 
nnet mean 250 : -0.3968034 
nnet RMSE 250 : 0.1569534 


s: 251 
logit 251 : -0.5179996 
logit mean 251 : -0.4711349 
logit RMSE 251 : 0.08932131 

boosting 251 : -0.7166077 
boosting mean 251 : -0.4593648 
boosting RMSE 251 : 0.1558537 

forest 251 : -0.4181446 
forest mean 251 : -0.4157324 
forest RMSE 251 : 0.06052107 

nnet 251 : -0.4040512 
nnet mean 251 : -0.3968323 
nnet RMSE 251 : 0.1566406 


s: 252 
logit 252 : -0.4780198 
logit mean 252 : -0.4711622 
logit RMSE 252 : 0.0892793 

boosting 252 : -0.551634 
boosting mean 252 : -0.4597310 
boosting RMSE 252 : 0.1558372 

forest 252 : -0.3407805 
forest mean 252 : -0.415435 
forest RMSE 252 : 0.06051596 

nnet 252 : -0.3427634 
nnet mean 252 : -0.3966177 
nnet RMSE 252 : 0.1563711 


s: 253 
logit 253 : -0.4711106 
logit mean 253 : -0.471162 
logit RMSE 253 : 0.08921476 

boosting 253 : -0.4569389 
boosting mean 253 : -0.4597199 
boosting RMSE 253 : 0.1555701 

forest 253 : -0.4603317 
forest mean 253 : -0.4156124 
forest RMSE 253 : 0.06051523 

nnet 253 : -0.3838946 
nnet mean 253 : -0.3965674 
nnet RMSE 253 : 0.1560650 


s: 254 
logit 254 : -0.4399387 
logit mean 254 : -0.4710391 
logit RMSE 254 : 0.08907423 

boosting 254 : -0.440898 
boosting mean 254 : -0.4596458 
boosting RMSE 254 : 0.1552848 

forest 254 : -0.4702748 
forest mean 254 : -0.4158276 
forest RMSE 254 : 0.06055674 

nnet 254 : -0.4065619 
nnet mean 254 : -0.3966068 
nnet RMSE 254 : 0.1557581 


s: 255 
logit 255 : -0.3912638 
logit mean 255 : -0.4707262 
logit RMSE 255 : 0.08890108 

boosting 255 : -0.4672323 
boosting mean 255 : -0.4596756 
boosting RMSE 255 : 0.1550372 

forest 255 : -0.45922 
forest mean 255 : -0.4159978 
forest RMSE 255 : 0.06055155 

nnet 255 : -0.5588379 
nnet mean 255 : -0.397243 
nnet RMSE 255 : 0.1557703 


s: 256 
logit 256 : -0.4148386 
logit mean 256 : -0.4705079 
logit RMSE 256 : 0.08873213 

boosting 256 : -0.4293029 
boosting mean 256 : -0.4595569 
boosting RMSE 256 : 0.1547449 

forest 256 : -0.4195907 
forest mean 256 : -0.4160118 
forest RMSE 256 : 0.06044557 

nnet 256 : -0.3289017 
nnet mean 256 : -0.396976 
nnet RMSE 256 : 0.1555292 


s: 257 
logit 257 : -0.4950125 
logit mean 257 : -0.4706032 
logit RMSE 257 : 0.08875743 

boosting 257 : -0.4953417 
boosting mean 257 : -0.4596962 
boosting RMSE 257 : 0.1545580 

forest 257 : -0.4374711 
forest mean 257 : -0.4160953 
forest RMSE 257 : 0.06037312 

nnet 257 : -0.7713137 
nnet mean 257 : -0.3984326 
nnet RMSE 257 : 0.1569449 


s: 258 
logit 258 : -0.4885754 
logit mean 258 : -0.4706729 
logit RMSE 258 : 0.08875672 

boosting 258 : -0.5459366 
boosting mean 258 : -0.4600304 
boosting RMSE 258 : 0.1545255 

forest 258 : -0.4463336 
forest mean 258 : -0.4162125 
forest RMSE 258 : 0.06032502 

nnet 258 : -0.3239928 
nnet mean 258 : -0.3981441 
nnet RMSE 258 : 0.1567119 


s: 259 
logit 259 : -0.5631648 
logit mean 259 : -0.47103 
logit RMSE 259 : 0.0891635 

boosting 259 : -0.4509408 
boosting mean 259 : -0.4599953 
boosting RMSE 259 : 0.1542594 

forest 259 : -0.4283918 
forest mean 259 : -0.4162596 
forest RMSE 259 : 0.06023429 

nnet 259 : -0.6915982 
nnet mean 259 : -0.3992771 
nnet RMSE 259 : 0.1574550 


s: 260 
logit 260 : -0.4718291 
logit mean 260 : -0.4710331 
logit RMSE 260 : 0.08910329 

boosting 260 : -0.4472727 
boosting mean 260 : -0.4599464 
boosting RMSE 260 : 0.1539904 

forest 260 : -0.3866234 
forest mean 260 : -0.4161456 
forest RMSE 260 : 0.06012406 

nnet 260 : -0.4354017 
nnet mean 260 : -0.399416 
nnet RMSE 260 : 0.1571673 


s: 261 
logit 261 : -0.4609397 
logit mean 261 : -0.4709944 
logit RMSE 261 : 0.0890124 

boosting 261 : -0.4433627 
boosting mean 261 : -0.4598829 
boosting RMSE 261 : 0.1537185 

forest 261 : -0.431554 
forest mean 261 : -0.4162046 
forest RMSE 261 : 0.06004055 

nnet 261 : -0.3316883 
nnet mean 261 : -0.3991565 
nnet RMSE 261 : 0.1569229 


s: 262 
logit 262 : -0.4918611 
logit mean 262 : -0.4710741 
logit RMSE 262 : 0.08902344 

boosting 262 : -0.5016395 
boosting mean 262 : -0.4600422 
boosting RMSE 262 : 0.1535533 

forest 262 : -0.4398963 
forest mean 262 : -0.416295 
forest RMSE 262 : 0.05997653 

nnet 262 : -0.6452208 
nnet mean 262 : -0.4000957 
nnet RMSE 262 : 0.1573541 


s: 263 
logit 263 : -0.5151644 
logit mean 263 : -0.4712417 
logit RMSE 263 : 0.08913735 

boosting 263 : -0.2921135 
boosting mean 263 : -0.4594037 
boosting RMSE 263 : 0.1534054 

forest 263 : -0.4441192 
forest mean 263 : -0.4164008 
forest RMSE 263 : 0.05992418 

nnet 263 : -0.509197 
nnet mean 263 : -0.4005106 
nnet RMSE 263 : 0.1571990 


s: 264 
logit 264 : -0.4983429 
logit mean 264 : -0.4713444 
logit RMSE 264 : 0.08917402 

boosting 264 : -0.4536513 
boosting mean 264 : -0.4593819 
boosting RMSE 264 : 0.1531502 

forest 264 : -0.4292248 
forest mean 264 : -0.4164494 
forest RMSE 264 : 0.05983762 

nnet 264 : -0.3578607 
nnet mean 264 : -0.400349 
nnet RMSE 264 : 0.1569224 


s: 265 
logit 265 : -0.4780719 
logit mean 265 : -0.4713697 
logit RMSE 265 : 0.08913472 

boosting 265 : -0.4246467 
boosting mean 265 : -0.4592509 
boosting RMSE 265 : 0.1528685 

forest 265 : -0.3888329 
forest mean 265 : -0.4163452 
forest RMSE 265 : 0.05972855 

nnet 265 : -0.6587667 
nnet mean 265 : -0.4013242 
nnet RMSE 265 : 0.1574306 


s: 266 
logit 266 : -0.5073175 
logit mean 266 : -0.4715049 
logit RMSE 266 : 0.08921002 

boosting 266 : -0.6627636 
boosting mean 266 : -0.4600159 
boosting RMSE 266 : 0.1534291 

forest 266 : -0.419336 
forest mean 266 : -0.4163564 
forest RMSE 266 : 0.05962796 

nnet 266 : -0.2870992 
nnet mean 266 : -0.4008947 
nnet RMSE 266 : 0.1572868 


s: 267 
logit 267 : -0.4473667 
logit mean 267 : -0.4714145 
logit RMSE 267 : 0.08908997 

boosting 267 : -0.3953367 
boosting mean 267 : -0.4597737 
boosting RMSE 267 : 0.1531418 

forest 267 : -0.3937342 
forest mean 267 : -0.4162717 
forest RMSE 267 : 0.05951743 

nnet 267 : -0.5084152 
nnet mean 267 : -0.4012974 
nnet RMSE 267 : 0.1571321 


s: 268 
logit 268 : -0.5959178 
logit mean 268 : -0.4718791 
logit RMSE 268 : 0.0897253 

boosting 268 : -0.3948288 
boosting mean 268 : -0.4595314 
boosting RMSE 268 : 0.1528561 

forest 268 : -0.5141923 
forest mean 268 : -0.4166371 
forest RMSE 268 : 0.0598144 

nnet 268 : -0.6911318 
nnet mean 268 : -0.4023789 
nnet RMSE 268 : 0.1578437 


s: 269 
logit 269 : -0.4382292 
logit mean 269 : -0.471754 
logit RMSE 269 : 0.0895887 

boosting 269 : -0.6933763 
boosting mean 269 : -0.4604007 
boosting RMSE 269 : 0.1536167 

forest 269 : -0.4123711 
forest mean 269 : -0.4166212 
forest RMSE 269 : 0.05970789 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 269 : -0.1899319 
nnet mean 269 : -0.4015891 
nnet RMSE 269 : 0.1580698 


s: 270 
logit 270 : -0.4162414 
logit mean 270 : -0.4715484 
logit RMSE 270 : 0.0894281 

boosting 270 : -0.4532847 
boosting mean 270 : -0.4603743 
boosting RMSE 270 : 0.1533663 

forest 270 : -0.381279 
forest mean 270 : -0.4164903 
forest RMSE 270 : 0.0596081 

nnet 270 : -0.436535 
nnet mean 270 : -0.4017186 
nnet RMSE 270 : 0.1577925 


s: 271 
logit 271 : -0.4120680 
logit mean 271 : -0.4713289 
logit RMSE 271 : 0.08926597 

boosting 271 : -0.5418653 
boosting mean 271 : -0.460675 
boosting RMSE 271 : 0.1533254 

forest 271 : -0.5349479 
forest mean 271 : -0.4169274 
forest RMSE 271 : 0.06006008 

nnet 271 : -0.2694847 
nnet mean 271 : -0.4012306 
nnet RMSE 271 : 0.1577005 


s: 272 
logit 272 : -0.3814769 
logit mean 272 : -0.4709985 
logit RMSE 272 : 0.0891088 

boosting 272 : -0.6416107 
boosting mean 272 : -0.4613402 
boosting RMSE 272 : 0.1537429 

forest 272 : -0.4786425 
forest mean 272 : -0.4171543 
forest RMSE 272 : 0.06013892 

nnet 272 : -0.4210763 
nnet mean 272 : -0.4013036 
nnet RMSE 272 : 0.1574155 


s: 273 
logit 273 : -0.4870934 
logit mean 273 : -0.4710575 
logit RMSE 273 : 0.0891015 

boosting 273 : -0.7678731 
boosting mean 273 : -0.4624631 
boosting RMSE 273 : 0.1550678 

forest 273 : -0.3408014 
forest mean 273 : -0.4168747 
forest RMSE 273 : 0.0601355 

nnet 273 : -0.3852522 
nnet mean 273 : -0.4012448 
nnet RMSE 273 : 0.1571295 


s: 274 
logit 274 : -0.5151656 
logit mean 274 : -0.4712185 
logit RMSE 274 : 0.08921047 

boosting 274 : -0.3115735 
boosting mean 274 : -0.4619124 
boosting RMSE 274 : 0.1548767 

forest 274 : -0.3608609 
forest mean 274 : -0.4166702 
forest RMSE 274 : 0.06007222 

nnet 274 : -0.3666772 
nnet mean 274 : -0.4011186 
nnet RMSE 274 : 0.1568554 


s: 275 
logit 275 : -0.4104862 
logit mean 275 : -0.4709976 
logit RMSE 275 : 0.08905037 

boosting 275 : -0.4529808 
boosting mean 275 : -0.4618799 
boosting RMSE 275 : 0.1546278 

forest 275 : -0.4425806 
forest mean 275 : -0.4167644 
forest RMSE 275 : 0.06001785 

nnet 275 : -0.4393091 
nnet mean 275 : -0.4012575 
nnet RMSE 275 : 0.1565879 


s: 276 
logit 276 : -0.4429082 
logit mean 276 : -0.4708958 
logit RMSE 276 : 0.08892642 

boosting 276 : -0.2840746 
boosting mean 276 : -0.4612357 
boosting RMSE 276 : 0.1545051 

forest 276 : -0.3009989 
forest mean 276 : -0.416345 
forest RMSE 276 : 0.06020467 

nnet 276 : -0.1409291 
nnet mean 276 : -0.4003143 
nnet RMSE 276 : 0.1570800 


s: 277 
logit 277 : -0.492344 
logit mean 277 : -0.4709733 
logit RMSE 277 : 0.08893899 

boosting 277 : -0.407657 
boosting mean 277 : -0.4610422 
boosting RMSE 277 : 0.1542267 

forest 277 : -0.3409724 
forest mean 277 : -0.4160729 
forest RMSE 277 : 0.06020046 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 277 : -0.3326983 
nnet mean 277 : -0.4000702 
nnet RMSE 277 : 0.1568483 


s: 278 
logit 278 : -0.5089717 
logit mean 278 : -0.47111 
logit RMSE 278 : 0.08901913 

boosting 278 : -0.3838372 
boosting mean 278 : -0.4607645 
boosting RMSE 278 : 0.1539521 

forest 278 : -0.3947039 
forest mean 278 : -0.415996 
forest RMSE 278 : 0.06009293 

nnet 278 : -0.432541 
nnet mean 278 : -0.400187 
nnet RMSE 278 : 0.1565781 


s: 279 
logit 279 : -0.5389304 
logit mean 279 : -0.4713530 
logit RMSE 279 : 0.08924788 

boosting 279 : -0.2610010 
boosting mean 279 : -0.4600485 
boosting RMSE 279 : 0.1539011 

forest 279 : -0.3788321 
forest mean 279 : -0.4158628 
forest RMSE 279 : 0.05999852 

nnet 279 : -0.276938 
nnet mean 279 : -0.3997452 
nnet RMSE 279 : 0.1564708 


s: 280 
logit 280 : -0.3948507 
logit mean 280 : -0.4710798 
logit RMSE 280 : 0.0890889 

boosting 280 : -0.3601704 
boosting mean 280 : -0.4596918 
boosting RMSE 280 : 0.1536444 

forest 280 : -0.4370969 
forest mean 280 : -0.4159387 
forest RMSE 280 : 0.05993231 

nnet 280 : -0.4870183 
nnet mean 280 : -0.4000569 
nnet RMSE 280 : 0.1562777 


s: 281 
logit 281 : -0.3942388 
logit mean 281 : -0.4708064 
logit RMSE 281 : 0.0889309 

boosting 281 : -0.5264528 
boosting mean 281 : -0.4599294 
boosting RMSE 281 : 0.1535562 

forest 281 : -0.3829372 
forest mean 281 : -0.4158212 
forest RMSE 281 : 0.05983423 

nnet 281 : -0.1955893 
nnet mean 281 : -0.3993293 
nnet RMSE 281 : 0.1564752 


s: 282 
logit 282 : -0.4394406 
logit mean 282 : -0.4706951 
logit RMSE 282 : 0.08880414 

boosting 282 : -0.3255565 
boosting mean 282 : -0.4594529 
boosting RMSE 282 : 0.1533478 

forest 282 : -0.3215827 
forest mean 282 : -0.415487 
forest RMSE 282 : 0.05991031 

nnet 282 : -0.3782738 
nnet mean 282 : -0.3992546 
nnet RMSE 282 : 0.1562029 


s: 283 
logit 283 : -0.4216059 
logit mean 283 : -0.4705217 
logit RMSE 283 : 0.08865641 

boosting 283 : -0.2114095 
boosting mean 283 : -0.4585764 
boosting RMSE 283 : 0.1534866 

forest 283 : -0.3892867 
forest mean 283 : -0.4153945 
forest RMSE 283 : 0.05980776 

nnet 283 : -0.4923609 
nnet mean 283 : -0.3995836 
nnet RMSE 283 : 0.1560233 


s: 284 
logit 284 : -0.5310634 
logit mean 284 : -0.4707349 
logit RMSE 284 : 0.08884125 

boosting 284 : -0.2547913 
boosting mean 284 : -0.4578589 
boosting RMSE 284 : 0.1534582 

forest 284 : -0.2647238 
forest mean 284 : -0.4148639 
forest RMSE 284 : 0.06023959 

nnet 284 : -0.2587212 
nnet mean 284 : -0.3990876 
nnet RMSE 284 : 0.1559738 


s: 285 
logit 285 : -0.4853043 
logit mean 285 : -0.470786 
logit RMSE 285 : 0.08882909 

boosting 285 : -0.5733116 
boosting mean 285 : -0.458264 
boosting RMSE 285 : 0.1535324 

forest 285 : -0.2603836 
forest mean 285 : -0.4143219 
forest RMSE 285 : 0.06069985 

nnet 285 : -0.1357094 
nnet mean 285 : -0.3981635 
nnet RMSE 285 : 0.1564850 


s: 286 
logit 286 : -0.3702658 
logit mean 286 : -0.4704345 
logit RMSE 286 : 0.08869108 

boosting 286 : -0.6450343 
boosting mean 286 : -0.458917 
boosting RMSE 286 : 0.1539471 

forest 286 : -0.439329 
forest mean 286 : -0.4144093 
forest RMSE 286 : 0.06063825 

nnet 286 : -0.2085490 
nnet mean 286 : -0.3975005 
nnet RMSE 286 : 0.1566209 


s: 287 
logit 287 : -0.4713027 
logit mean 287 : -0.4704375 
logit RMSE 287 : 0.08863642 

boosting 287 : -0.3305261 
boosting mean 287 : -0.4584697 
boosting RMSE 287 : 0.1537333 

forest 287 : -0.3672671 
forest mean 287 : -0.4142451 
forest RMSE 287 : 0.06056334 

nnet 287 : -0.4510032 
nnet mean 287 : -0.3976869 
nnet RMSE 287 : 0.1563768 


s: 288 
logit 288 : -0.4779286 
logit mean 288 : -0.4704635 
logit RMSE 288 : 0.08860148 

boosting 288 : -0.4975971 
boosting mean 288 : -0.4586055 
boosting RMSE 288 : 0.1535739 

forest 288 : -0.4448289 
forest mean 288 : -0.4143513 
forest RMSE 288 : 0.06051579 

nnet 288 : -0.5009025 
nnet mean 288 : -0.3980453 
nnet RMSE 288 : 0.1562182 


s: 289 
logit 289 : -0.3671493 
logit mean 289 : -0.4701061 
logit RMSE 289 : 0.08846916 

boosting 289 : -0.2358267 
boosting mean 289 : -0.4578347 
boosting RMSE 289 : 0.1536119 

forest 289 : -0.4296507 
forest mean 289 : -0.4144042 
forest RMSE 289 : 0.06043617 

nnet 289 : -0.3011253 
nnet mean 289 : -0.3977099 
nnet RMSE 289 : 0.1560561 


s: 290 
logit 290 : -0.4963958 
logit mean 290 : -0.4701967 
logit RMSE 290 : 0.08849772 

boosting 290 : -0.5365816 
boosting mean 290 : -0.4581062 
boosting RMSE 290 : 0.1535564 

forest 290 : -0.4602456 
forest mean 290 : -0.4145623 
forest RMSE 290 : 0.06043551 

nnet 290 : -0.4393039 
nnet mean 290 : -0.3978534 
nnet RMSE 290 : 0.1558039 


s: 291 
logit 291 : -0.4954389 
logit mean 291 : -0.4702835 
logit RMSE 291 : 0.0885225 

boosting 291 : -0.7756051 
boosting mean 291 : -0.4591973 
boosting RMSE 291 : 0.1548656 

forest 291 : -0.4424628 
forest mean 291 : -0.4146582 
forest RMSE 291 : 0.06038291 

nnet 291 : -0.3867569 
nnet mean 291 : -0.3978152 
nnet RMSE 291 : 0.1555379 


s: 292 
logit 292 : -0.5128303 
logit mean 292 : -0.4704292 
logit RMSE 292 : 0.08861713 

boosting 292 : -0.4306741 
boosting mean 292 : -0.4590996 
boosting RMSE 292 : 0.1546106 

forest 292 : -0.3552026 
forest mean 292 : -0.4144545 
forest RMSE 292 : 0.06033641 

nnet 292 : -0.2603079 
nnet mean 292 : -0.3973443 
nnet RMSE 292 : 0.1554864 


s: 293 
logit 293 : -0.4208665 
logit mean 293 : -0.47026 
logit RMSE 293 : 0.08847417 

boosting 293 : -0.6914553 
boosting mean 293 : -0.4598926 
boosting RMSE 293 : 0.1552829 

forest 293 : -0.4249088 
forest mean 293 : -0.4144902 
forest RMSE 293 : 0.06025093 

nnet 293 : -0.5702476 
nnet mean 293 : -0.3979344 
nnet RMSE 293 : 0.1555392 


s: 294 
logit 294 : -0.454952 
logit mean 294 : -0.4702079 
logit RMSE 294 : 0.0883817 

boosting 294 : -0.5387975 
boosting mean 294 : -0.460161 
boosting RMSE 294 : 0.1552298 

forest 294 : -0.3200590 
forest mean 294 : -0.414169 
forest RMSE 294 : 0.0603288 

nnet 294 : -0.4003149 
nnet mean 294 : -0.3979425 
nnet RMSE 294 : 0.1552745 


s: 295 
logit 295 : -0.4496458 
logit mean 295 : -0.4701382 
logit RMSE 295 : 0.08827911 

boosting 295 : -0.6734047 
boosting mean 295 : -0.4608838 
boosting RMSE 295 : 0.1557818 

forest 295 : -0.4454499 
forest mean 295 : -0.4142751 
forest RMSE 295 : 0.06028457 

nnet 295 : -0.3472663 
nnet mean 295 : -0.3977708 
nnet RMSE 295 : 0.1550415 


s: 296 
logit 296 : -0.4562532 
logit mean 296 : -0.4700913 
logit RMSE 296 : 0.0881905 

boosting 296 : -0.4625679 
boosting mean 296 : -0.4608895 
boosting RMSE 296 : 0.155561 

forest 296 : -0.2889816 
forest mean 296 : -0.4138518 
forest RMSE 296 : 0.0605276 

nnet 296 : -0.1743735 
nnet mean 296 : -0.397016 
nnet RMSE 296 : 0.1553339 


s: 297 
logit 297 : -0.4873002 
logit mean 297 : -0.4701493 
logit RMSE 297 : 0.08818751 

boosting 297 : -0.5995637 
boosting mean 297 : -0.4613565 
boosting RMSE 297 : 0.15573 

forest 297 : -0.4836418 
forest mean 297 : -0.4140868 
forest RMSE 297 : 0.06062021 

nnet 297 : -0.3493818 
nnet mean 297 : -0.3968556 
nnet RMSE 297 : 0.1551 


s: 298 
logit 298 : -0.4710004 
logit mean 298 : -0.4701521 
logit RMSE 298 : 0.08813544 

boosting 298 : -0.1759026 
boosting mean 298 : -0.4603986 
boosting RMSE 298 : 0.1560095 

forest 298 : -0.4377324 
forest mean 298 : -0.4141661 
forest RMSE 298 : 0.06055787 

nnet 298 : -0.3355303 
nnet mean 298 : -0.3966499 
nnet RMSE 298 : 0.1548846 


s: 299 
logit 299 : -0.5008317 
logit mean 299 : -0.4702547 
logit RMSE 299 : 0.08818095 

boosting 299 : -0.7251501 
boosting mean 299 : -0.461284 
boosting RMSE 299 : 0.1568795 

forest 299 : -0.4976752 
forest mean 299 : -0.4144454 
forest RMSE 299 : 0.06071984 

nnet 299 : -0.3616212 
nnet mean 299 : -0.3965327 
nnet RMSE 299 : 0.1546413 


s: 300 
logit 300 : -0.4954196 
logit mean 300 : -0.4703386 
logit RMSE 300 : 0.08820607 

boosting 300 : -0.5014161 
boosting mean 300 : -0.4614178 
boosting RMSE 300 : 0.1567272 

forest 300 : -0.4525306 
forest mean 300 : -0.4145724 
forest RMSE 300 : 0.06069438 

nnet 300 : -0.4907853 
nnet mean 300 : -0.3968469 
nnet RMSE 300 : 0.1544723 


s: 301 
logit 301 : -0.4418833 
logit mean 301 : -0.4702441 
logit RMSE 301 : 0.0880925 

boosting 301 : -0.5106875 
boosting mean 301 : -0.4615815 
boosting RMSE 301 : 0.1565966 

forest 301 : -0.488209 
forest mean 301 : -0.414817 
forest RMSE 301 : 0.0608064 

nnet 301 : -0.4117891 
nnet mean 301 : -0.3968965 
nnet RMSE 301 : 0.154217 


s: 302 
logit 302 : -0.4250518 
logit mean 302 : -0.4700944 
logit RMSE 302 : 0.08795835 

boosting 302 : -0.1341241 
boosting mean 302 : -0.4604972 
boosting RMSE 302 : 0.157084 

forest 302 : -0.3506175 
forest mean 302 : -0.4146044 
forest RMSE 302 : 0.06077212 

nnet 302 : -0.2786287 
nnet mean 302 : -0.3965049 
nnet RMSE 302 : 0.1541198 


s: 303 
logit 303 : -0.534807 
logit mean 303 : -0.470308 
logit RMSE 303 : 0.08815393 

boosting 303 : -0.5266413 
boosting mean 303 : -0.4607155 
boosting RMSE 303 : 0.1569932 

forest 303 : -0.4498542 
forest mean 303 : -0.4147207 
forest RMSE 303 : 0.06073931 

nnet 303 : -0.1634451 
nnet mean 303 : -0.3957357 
nnet RMSE 303 : 0.1544642 


s: 304 
logit 304 : -0.4786855 
logit mean 304 : -0.4703356 
logit RMSE 304 : 0.08812445 

boosting 304 : -0.6316861 
boosting mean 304 : -0.4612779 
boosting RMSE 304 : 0.1572971 

forest 304 : -0.4054124 
forest mean 304 : -0.4146901 
forest RMSE 304 : 0.06064013 

nnet 304 : -0.3459785 
nnet mean 304 : -0.3955721 
nnet RMSE 304 : 0.1542411 


s: 305 
logit 305 : -0.3782545 
logit mean 305 : -0.4700337 
logit RMSE 305 : 0.08798867 

boosting 305 : -0.3342791 
boosting mean 305 : -0.4608615 
boosting RMSE 305 : 0.1570841 

forest 305 : -0.5243314 
forest mean 305 : -0.4150496 
forest RMSE 305 : 0.06095778 

nnet 305 : -0.1478474 
nnet mean 305 : -0.3947598 
nnet RMSE 305 : 0.1546634 


s: 306 
logit 306 : -0.3791604 
logit mean 306 : -0.4697367 
logit RMSE 306 : 0.08785286 

boosting 306 : -0.3525852 
boosting mean 306 : -0.4605076 
boosting RMSE 306 : 0.1568506 

forest 306 : -0.4057114 
forest mean 306 : -0.4150191 
forest RMSE 306 : 0.06085897 

nnet 306 : -0.3920391 
nnet mean 306 : -0.3947510 
nnet RMSE 306 : 0.1544112 


s: 307 
logit 307 : -0.4997236 
logit mean 307 : -0.4698344 
logit RMSE 307 : 0.08789413 

boosting 307 : -0.3745337 
boosting mean 307 : -0.4602276 
boosting RMSE 307 : 0.1566017 

forest 307 : -0.4464933 
forest mean 307 : -0.4151216 
forest RMSE 307 : 0.06081769 

nnet 307 : -0.3650314 
nnet mean 307 : -0.3946541 
nnet RMSE 307 : 0.1541724 


s: 308 
logit 308 : -0.4723118 
logit mean 308 : -0.4698424 
logit RMSE 308 : 0.08784801 

boosting 308 : -0.4235901 
boosting mean 308 : -0.4601086 
boosting RMSE 308 : 0.1563531 

forest 308 : -0.4511402 
forest mean 308 : -0.4152386 
forest RMSE 308 : 0.06078876 

nnet 308 : -0.4745468 
nnet mean 308 : -0.3949135 
nnet RMSE 308 : 0.1539805 


s: 309 
logit 309 : -0.5096699 
logit mean 309 : -0.4699713 
logit RMSE 309 : 0.08792737 

boosting 309 : -0.5497407 
boosting mean 309 : -0.4603987 
boosting RMSE 309 : 0.1563321 

forest 309 : -0.4271576 
forest mean 309 : -0.4152771 
forest RMSE 309 : 0.06070998 

nnet 309 : -0.5351027 
nnet mean 309 : -0.3953672 
nnet RMSE 309 : 0.1539231 


s: 310 
logit 310 : -0.5162113 
logit mean 310 : -0.4701205 
logit RMSE 310 : 0.08803322 

boosting 310 : -0.9327977 
boosting mean 310 : -0.4619226 
boosting RMSE 310 : 0.1589862 

forest 310 : -0.4859597 
forest mean 310 : -0.4155051 
forest RMSE 310 : 0.06080829 

nnet 310 : -0.2232911 
nnet mean 310 : -0.3948121 
nnet RMSE 310 : 0.1540021 


s: 311 
logit 311 : -0.4447912 
logit mean 311 : -0.470039 
logit RMSE 311 : 0.08792826 

boosting 311 : -0.4371479 
boosting mean 311 : -0.4618429 
boosting RMSE 311 : 0.1587444 

forest 311 : -0.4054019 
forest mean 311 : -0.4154727 
forest RMSE 311 : 0.06071122 

nnet 311 : -0.5601051 
nnet mean 311 : -0.3953436 
nnet RMSE 311 : 0.1540221 


s: 312 
logit 312 : -0.398927 
logit mean 312 : -0.4698111 
logit RMSE 312 : 0.08778726 

boosting 312 : -0.4356482 
boosting mean 312 : -0.461759 
boosting RMSE 312 : 0.1585026 

forest 312 : -0.4329747 
forest mean 312 : -0.4155287 
forest RMSE 312 : 0.06064259 

nnet 312 : -0.4031986 
nnet mean 312 : -0.3953688 
nnet RMSE 312 : 0.1537752 


s: 313 
logit 313 : -0.4636617 
logit mean 313 : -0.4697914 
logit RMSE 313 : 0.08772075 

boosting 313 : -0.5485228 
boosting mean 313 : -0.4620362 
boosting RMSE 313 : 0.1584717 

forest 313 : -0.4253395 
forest mean 313 : -0.4155601 
forest RMSE 313 : 0.06056258 

nnet 313 : -0.5223954 
nnet mean 313 : -0.3957746 
nnet RMSE 313 : 0.1536851 


s: 314 
logit 314 : -0.4005141 
logit mean 314 : -0.4695708 
logit RMSE 314 : 0.08758096 

boosting 314 : -0.4695901 
boosting mean 314 : -0.4620602 
boosting RMSE 314 : 0.1582679 

forest 314 : -0.351061 
forest mean 314 : -0.4153547 
forest RMSE 314 : 0.0605291 

nnet 314 : -0.6060566 
nnet mean 314 : -0.3964443 
nnet RMSE 314 : 0.1538802 


s: 315 
logit 315 : -0.418514 
logit mean 315 : -0.4694087 
logit RMSE 315 : 0.08744805 

boosting 315 : -0.5935493 
boosting mean 315 : -0.4624777 
boosting RMSE 315 : 0.1583924 

forest 315 : -0.3999823 
forest mean 315 : -0.4153059 
forest RMSE 315 : 0.06043295 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 315 : -0.1975695 
nnet mean 315 : -0.395813 
nnet RMSE 315 : 0.1540585 


s: 316 
logit 316 : -0.4531432 
logit mean 316 : -0.4693573 
logit RMSE 316 : 0.08736074 

boosting 316 : -0.5160014 
boosting mean 316 : -0.462647 
boosting RMSE 316 : 0.1582761 

forest 316 : -0.4795256 
forest mean 316 : -0.4155091 
forest RMSE 316 : 0.06050287 

nnet 316 : -0.2706378 
nnet mean 316 : -0.3954169 
nnet RMSE 316 : 0.1539866 


s: 317 
logit 317 : -0.44145 
logit mean 317 : -0.4692692 
logit RMSE 317 : 0.0872539 

boosting 317 : -0.695703 
boosting mean 317 : -0.4633822 
boosting RMSE 317 : 0.1588966 

forest 317 : -0.3531501 
forest mean 317 : -0.4153124 
forest RMSE 317 : 0.06046465 

nnet 317 : -0.2086213 
nnet mean 317 : -0.3948276 
nnet RMSE 317 : 0.1541188 


s: 318 
logit 318 : -0.478947 
logit mean 318 : -0.4692997 
logit RMSE 318 : 0.08722902 

boosting 318 : -0.4198921 
boosting mean 318 : -0.4632455 
boosting RMSE 318 : 0.1586505 

forest 318 : -0.3874557 
forest mean 318 : -0.4152248 
forest RMSE 318 : 0.0603736 

nnet 318 : -0.2217871 
nnet mean 318 : -0.3942834 
nnet RMSE 318 : 0.1542005 


s: 319 
logit 319 : -0.4437406 
logit mean 319 : -0.4692195 
logit RMSE 319 : 0.08712662 

boosting 319 : -0.3923069 
boosting mean 319 : -0.4630231 
boosting RMSE 319 : 0.1584022 

forest 319 : -0.4026253 
forest mean 319 : -0.4151853 
forest RMSE 319 : 0.06027908 

nnet 319 : -0.456281 
nnet mean 319 : -0.3944778 
nnet RMSE 319 : 0.1539909 


s: 320 
logit 320 : -0.4747504 
logit mean 320 : -0.4692368 
logit RMSE 320 : 0.08709068 

boosting 320 : -0.4386322 
boosting mean 320 : -0.4629469 
boosting RMSE 320 : 0.1581693 

forest 320 : -0.535516 
forest mean 320 : -0.4155613 
forest RMSE 320 : 0.06065972 

nnet 320 : -0.4336864 
nnet mean 320 : -0.3946003 
nnet RMSE 320 : 0.1537616 


s: 321 
logit 321 : -0.4640478 
logit mean 321 : -0.4692207 
logit RMSE 321 : 0.08702837 

boosting 321 : -0.357801 
boosting mean 321 : -0.4626193 
boosting RMSE 321 : 0.1579403 

forest 321 : -0.4917784 
forest mean 321 : -0.4157988 
forest RMSE 321 : 0.06078141 

nnet 321 : -0.4553638 
nnet mean 321 : -0.3947896 
nnet RMSE 321 : 0.153553 


s: 322 
logit 322 : -0.4103910 
logit mean 322 : -0.469038 
logit RMSE 322 : 0.08689506 

boosting 322 : -0.52943 
boosting mean 322 : -0.4628268 
boosting RMSE 322 : 0.1578597 

forest 322 : -0.3161164 
forest mean 322 : -0.4154892 
forest RMSE 322 : 0.06086673 

nnet 322 : -0.4584628 
nnet mean 322 : -0.3949874 
nnet RMSE 322 : 0.153349 


s: 323 
logit 323 : -0.4405988 
logit mean 323 : -0.4689499 
logit RMSE 323 : 0.08678984 

boosting 323 : -0.1436244 
boosting mean 323 : -0.4618385 
boosting RMSE 323 : 0.1582594 

forest 323 : -0.5573645 
forest mean 323 : -0.4159284 
forest RMSE 323 : 0.06139997 

nnet 323 : -0.3870767 
nnet mean 323 : -0.3949629 
nnet RMSE 323 : 0.1531131 


s: 324 
logit 324 : -0.3955375 
logit mean 324 : -0.4687233 
logit RMSE 324 : 0.08665616 

boosting 324 : -0.3524970 
boosting mean 324 : -0.4615011 
boosting RMSE 324 : 0.158037 

forest 324 : -0.3769771 
forest mean 324 : -0.4158082 
forest RMSE 324 : 0.06131848 

nnet 324 : -0.3927892 
nnet mean 324 : -0.3949562 
nnet RMSE 324 : 0.1528772 


s: 325 
logit 325 : -0.4425097 
logit mean 325 : -0.4686427 
logit RMSE 325 : 0.08655487 

boosting 325 : -0.4127584 
boosting mean 325 : -0.4613511 
boosting RMSE 325 : 0.1577953 

forest 325 : -0.4172918 
forest mean 325 : -0.4158128 
forest RMSE 325 : 0.06123159 

nnet 325 : -0.3316866 
nnet mean 325 : -0.3947615 
nnet RMSE 325 : 0.1526888 


s: 326 
logit 326 : -0.4439338 
logit mean 326 : -0.4685669 
logit RMSE 326 : 0.08645626 

boosting 326 : -0.4744007 
boosting mean 326 : -0.4613911 
boosting RMSE 326 : 0.1576069 

forest 326 : -0.4232084 
forest mean 326 : -0.4158355 
forest RMSE 326 : 0.06115111 

nnet 326 : -0.3354943 
nnet mean 326 : -0.3945797 
nnet RMSE 326 : 0.1524963 


s: 327 
logit 327 : -0.4946401 
logit mean 327 : -0.4686466 
logit RMSE 327 : 0.08648247 

boosting 327 : -0.451198 
boosting mean 327 : -0.4613600 
boosting RMSE 327 : 0.1573912 

forest 327 : -0.4251466 
forest mean 327 : -0.4158639 
forest RMSE 327 : 0.06107337 

nnet 327 : -0.1676673 
nnet mean 327 : -0.3938858 
nnet RMSE 327 : 0.1528041 


s: 328 
logit 328 : -0.4739304 
logit mean 328 : -0.4686627 
logit RMSE 328 : 0.08644697 

boosting 328 : -0.5286314 
boosting mean 328 : -0.4615650 
boosting RMSE 328 : 0.1573115 

forest 328 : -0.5219136 
forest mean 328 : -0.4161873 
forest RMSE 328 : 0.06135062 

nnet 328 : -0.3715656 
nnet mean 328 : -0.3938177 
nnet RMSE 328 : 0.1525790 


s: 329 
logit 329 : -0.3910346 
logit mean 329 : -0.4684268 
logit RMSE 329 : 0.0863169 

boosting 329 : -0.5205497 
boosting mean 329 : -0.4617443 
boosting RMSE 329 : 0.1572128 

forest 329 : -0.4038226 
forest mean 329 : -0.4161497 
forest RMSE 329 : 0.06125768 

nnet 329 : -0.4307018 
nnet mean 329 : -0.3939298 
nnet RMSE 329 : 0.1523564 


s: 330 
logit 330 : -0.4167432 
logit mean 330 : -0.4682702 
logit RMSE 330 : 0.08619095 

boosting 330 : -0.4089254 
boosting mean 330 : -0.4615843 
boosting RMSE 330 : 0.1569752 

forest 330 : -0.3736188 
forest mean 330 : -0.4160208 
forest RMSE 330 : 0.06118203 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 330 : -0.2304616 
nnet mean 330 : -0.3934345 
nnet RMSE 330 : 0.1524114 


s: 331 
logit 331 : -0.4078769 
logit mean 331 : -0.4680877 
logit RMSE 331 : 0.08606174 

boosting 331 : -0.783486 
boosting mean 331 : -0.4625568 
boosting RMSE 331 : 0.1581489 

forest 331 : -0.495445 
forest mean 331 : -0.4162607 
forest RMSE 331 : 0.06131438 

nnet 331 : -0.3468783 
nnet mean 331 : -0.3932938 
nnet RMSE 331 : 0.1522090 


s: 332 
logit 332 : -0.4951054 
logit mean 332 : -0.4681691 
logit RMSE 332 : 0.08609041 

boosting 332 : -0.4448195 
boosting mean 332 : -0.4625034 
boosting RMSE 332 : 0.1579297 

forest 332 : -0.375821 
forest mean 332 : -0.4161389 
forest RMSE 332 : 0.06123635 

nnet 332 : -0.5608991 
nnet mean 332 : -0.3937986 
nnet RMSE 332 : 0.1522359 


s: 333 
logit 333 : -0.4586514 
logit mean 333 : -0.4681405 
logit RMSE 333 : 0.08602111 

boosting 333 : -0.3379248 
boosting mean 333 : -0.4621293 
boosting RMSE 333 : 0.1577291 

forest 333 : -0.4876696 
forest mean 333 : -0.4163537 
forest RMSE 333 : 0.06133279 

nnet 333 : -0.6380722 
nnet mean 333 : -0.3945322 
nnet RMSE 333 : 0.1525660 


s: 334 
logit 334 : -0.4427507 
logit mean 334 : -0.4680645 
logit RMSE 334 : 0.0859241 

boosting 334 : -0.4423078 
boosting mean 334 : -0.4620699 
boosting RMSE 334 : 0.1575098 

forest 334 : -0.4232574 
forest mean 334 : -0.4163744 
forest RMSE 334 : 0.06125413 

nnet 334 : -0.3413068 
nnet mean 334 : -0.3943728 
nnet RMSE 334 : 0.1523713 


s: 335 
logit 335 : -0.4466549 
logit mean 335 : -0.4680006 
logit RMSE 335 : 0.08583361 

boosting 335 : -0.387653 
boosting mean 335 : -0.4618478 
boosting RMSE 335 : 0.1572760 

forest 335 : -0.4887774 
forest mean 335 : -0.4165905 
forest RMSE 335 : 0.06135466 

nnet 335 : -0.6537926 
nnet mean 335 : -0.3951472 
nnet RMSE 335 : 0.1527742 


s: 336 
logit 336 : -0.4924114 
logit mean 336 : -0.4680732 
logit RMSE 336 : 0.08585393 

boosting 336 : -0.5800413 
boosting mean 336 : -0.4621995 
boosting RMSE 336 : 0.1573486 

forest 336 : -0.4618327 
forest mean 336 : -0.4167252 
forest RMSE 336 : 0.06135609 

nnet 336 : -0.3934125 
nnet mean 336 : -0.3951421 
nnet RMSE 336 : 0.1525471 


s: 337 
logit 337 : -0.4778821 
logit mean 337 : -0.4681023 
logit RMSE 337 : 0.08583137 

boosting 337 : -0.4061415 
boosting mean 337 : -0.4620332 
boosting RMSE 337 : 0.1571153 

forest 337 : -0.4963086 
forest mean 337 : -0.4169613 
forest RMSE 337 : 0.0614892 

nnet 337 : -0.600138 
nnet mean 337 : -0.3957504 
nnet RMSE 337 : 0.1527103 


s: 338 
logit 338 : -0.3664188 
logit mean 338 : -0.4678015 
logit RMSE 338 : 0.08572377 

boosting 338 : -0.5382101 
boosting mean 338 : -0.4622586 
boosting RMSE 338 : 0.1570627 

forest 338 : -0.3788410 
forest mean 338 : -0.4168486 
forest RMSE 338 : 0.06140896 

nnet 338 : -0.4764018 
nnet mean 338 : -0.395989 
nnet RMSE 338 : 0.1525409 


s: 339 
logit 339 : -0.4836046 
logit mean 339 : -0.4678481 
logit RMSE 339 : 0.0857176 

boosting 339 : -0.4541708 
boosting mean 339 : -0.4622347 
boosting RMSE 339 : 0.1568585 

forest 339 : -0.366028 
forest mean 339 : -0.4166987 
forest RMSE 339 : 0.06134607 

nnet 339 : -0.3743037 
nnet mean 339 : -0.395925 
nnet RMSE 339 : 0.1523221 


s: 340 
logit 340 : -0.4342602 
logit mean 340 : -0.4677493 
logit RMSE 340 : 0.08561161 

boosting 340 : -0.3205196 
boosting mean 340 : -0.4618179 
boosting RMSE 340 : 0.1566870 

forest 340 : -0.4605522 
forest mean 340 : -0.4168276 
forest RMSE 340 : 0.06134375 

nnet 340 : -0.5183656 
nnet mean 340 : -0.3962851 
nnet RMSE 340 : 0.1522333 


s: 341 
logit 341 : -0.4390488 
logit mean 341 : -0.4676651 
logit RMSE 341 : 0.08551214 

boosting 341 : -0.755141 
boosting mean 341 : -0.4626781 
boosting RMSE 341 : 0.1576346 

forest 341 : -0.3713825 
forest mean 341 : -0.4166944 
forest RMSE 341 : 0.06127334 

nnet 341 : -0.5120066 
nnet mean 341 : -0.3966245 
nnet RMSE 341 : 0.1521309 


s: 342 
logit 342 : -0.4730094 
logit mean 342 : -0.4676808 
logit RMSE 342 : 0.08547825 

boosting 342 : -0.7558442 
boosting mean 342 : -0.4635353 
boosting RMSE 342 : 0.1585758 

forest 342 : -0.3844884 
forest mean 342 : -0.4166002 
forest RMSE 342 : 0.06118945 

nnet 342 : -0.5239421 
nnet mean 342 : -0.3969968 
nnet RMSE 342 : 0.1520561 


s: 343 
logit 343 : -0.4879059 
logit mean 343 : -0.4677397 
logit RMSE 343 : 0.08548543 

boosting 343 : -0.6976671 
boosting mean 343 : -0.4642179 
boosting RMSE 343 : 0.1591580 

forest 343 : -0.3836673 
forest mean 343 : -0.4165042 
forest RMSE 343 : 0.06110655 

nnet 343 : -0.5162843 
nnet mean 343 : -0.3973445 
nnet RMSE 343 : 0.1519641 


s: 344 
logit 344 : -0.4924804 
logit mean 344 : -0.4678117 
logit RMSE 344 : 0.0855066 

boosting 344 : -0.522009 
boosting mean 344 : -0.4643859 
boosting RMSE 344 : 0.1590626 

forest 344 : -0.5534289 
forest mean 344 : -0.4169022 
forest RMSE 344 : 0.06157586 

nnet 344 : -0.3799684 
nnet mean 344 : -0.397294 
nnet RMSE 344 : 0.1517469 


s: 345 
logit 345 : -0.4857287 
logit mean 345 : -0.4678636 
logit RMSE 345 : 0.08550724 

boosting 345 : -0.6261196 
boosting mean 345 : -0.4648547 
boosting RMSE 345 : 0.1592978 

forest 345 : -0.3316818 
forest mean 345 : -0.4166552 
forest RMSE 345 : 0.06159647 

nnet 345 : -0.3965105 
nnet mean 345 : -0.3972918 
nnet RMSE 345 : 0.1515269 


s: 346 
logit 346 : -0.4665387 
logit mean 346 : -0.4678598 
logit RMSE 346 : 0.08545848 

boosting 346 : -0.4425524 
boosting mean 346 : -0.4647902 
boosting RMSE 346 : 0.1590839 

forest 346 : -0.4039082 
forest mean 346 : -0.4166184 
forest RMSE 346 : 0.06150775 

nnet 346 : -0.6045625 
nnet mean 346 : -0.3978908 
nnet RMSE 346 : 0.1517069 


s: 347 
logit 347 : -0.4968012 
logit mean 347 : -0.4679432 
logit RMSE 347 : 0.08549333 

boosting 347 : -0.4419513 
boosting mean 347 : -0.4647244 
boosting RMSE 347 : 0.1588705 

forest 347 : -0.3958382 
forest mean 347 : -0.4165585 
forest RMSE 347 : 0.06141947 

nnet 347 : -0.5355142 
nnet mean 347 : -0.3982874 
nnet RMSE 347 : 0.1516627 


s: 348 
logit 348 : -0.517675 
logit mean 348 : -0.4680861 
logit RMSE 348 : 0.08560314 

boosting 348 : -0.5886761 
boosting mean 348 : -0.4650806 
boosting RMSE 348 : 0.1589641 

forest 348 : -0.5039795 
forest mean 348 : -0.4168097 
forest RMSE 348 : 0.06158392 

nnet 348 : -0.355992 
nnet mean 348 : -0.3981659 
nnet RMSE 348 : 0.1514630 


s: 349 
logit 349 : -0.4225024 
logit mean 349 : -0.4679555 
logit RMSE 349 : 0.0854889 

boosting 349 : -0.5025201 
boosting mean 349 : -0.4651879 
boosting RMSE 349 : 0.1588310 

forest 349 : -0.4473801 
forest mean 349 : -0.4168973 
forest RMSE 349 : 0.0615479 

nnet 349 : -0.3721283 
nnet mean 349 : -0.3980913 
nnet RMSE 349 : 0.1512532 


s: 350 
logit 350 : -0.4343471 
logit mean 350 : -0.4678594 
logit RMSE 350 : 0.08538642 

boosting 350 : -0.4551026 
boosting mean 350 : -0.4651591 
boosting RMSE 350 : 0.1586313 

forest 350 : -0.432348 
forest mean 350 : -0.4169414 
forest RMSE 350 : 0.06148423 

nnet 350 : -0.5317918 
nnet mean 350 : -0.3984733 
nnet RMSE 350 : 0.1512012 


s: 351 
logit 351 : -0.4671637 
logit mean 351 : -0.4678575 
logit RMSE 351 : 0.08534004 

boosting 351 : -0.5688237 
boosting mean 351 : -0.4654544 
boosting RMSE 351 : 0.1586613 

forest 351 : -0.4177225 
forest mean 351 : -0.4169437 
forest RMSE 351 : 0.06140387 

nnet 351 : -0.4090039 
nnet mean 351 : -0.3985033 
nnet RMSE 351 : 0.1509864 


s: 352 
logit 352 : -0.4435178 
logit mean 352 : -0.4677883 
logit RMSE 352 : 0.08525029 

boosting 352 : -0.4382998 
boosting mean 352 : -0.4653773 
boosting RMSE 352 : 0.1584489 

forest 352 : -0.4151696 
forest mean 352 : -0.4169386 
forest RMSE 352 : 0.06132192 

nnet 352 : -0.3397178 
nnet mean 352 : -0.3983363 
nnet RMSE 352 : 0.1508060 


s: 353 
logit 353 : -0.4040459 
logit mean 353 : -0.4676077 
logit RMSE 353 : 0.08512972 

boosting 353 : -0.5224321 
boosting mean 353 : -0.4655389 
boosting RMSE 353 : 0.1583584 

forest 353 : -0.3360254 
forest mean 353 : -0.4167094 
forest RMSE 353 : 0.0613296 

nnet 353 : -0.5282624 
nnet mean 353 : -0.3987043 
nnet RMSE 353 : 0.1507469 


s: 354 
logit 354 : -0.4530297 
logit mean 354 : -0.4675666 
logit RMSE 354 : 0.08505611 

boosting 354 : -0.5757006 
boosting mean 354 : -0.4658501 
boosting RMSE 354 : 0.1584101 

forest 354 : -0.3279361 
forest mean 354 : -0.4164586 
forest RMSE 354 : 0.06136257 

nnet 354 : -0.2483642 
nnet mean 354 : -0.3982796 
nnet RMSE 354 : 0.1507494 


s: 355 
logit 355 : -0.4120889 
logit mean 355 : -0.4674103 
logit RMSE 355 : 0.08493865 

boosting 355 : -0.3576949 
boosting mean 355 : -0.4655454 
boosting RMSE 355 : 0.1582028 

forest 355 : -0.3676741 
forest mean 355 : -0.4163212 
forest RMSE 355 : 0.06130009 

nnet 355 : -0.3650710 
nnet mean 355 : -0.3981861 
nnet RMSE 355 : 0.1505484 


s: 356 
logit 356 : -0.5618977 
logit mean 356 : -0.4676757 
logit RMSE 356 : 0.08525218 

boosting 356 : -0.3085729 
boosting mean 356 : -0.4651045 
boosting RMSE 356 : 0.1580547 

forest 356 : -0.3925546 
forest mean 356 : -0.4162544 
forest RMSE 356 : 0.06121521 

nnet 356 : -0.3140469 
nnet mean 356 : -0.3979497 
nnet RMSE 356 : 0.1504058 


s: 357 
logit 357 : -0.4706259 
logit mean 357 : -0.467684 
logit RMSE 357 : 0.08521472 

boosting 357 : -0.5394773 
boosting mean 357 : -0.4653128 
boosting RMSE 357 : 0.1580057 

forest 357 : -0.4043323 
forest mean 357 : -0.4162210 
forest RMSE 357 : 0.06112984 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 357 : -0.2996627 
nnet mean 357 : -0.3976744 
nnet RMSE 357 : 0.1502888 


s: 358 
logit 358 : -0.4864653 
logit mean 358 : -0.4677364 
logit RMSE 358 : 0.08521824 

boosting 358 : -0.4043893 
boosting mean 358 : -0.4651426 
boosting RMSE 358 : 0.1577851 

forest 358 : -0.4520727 
forest mean 358 : -0.4163212 
forest RMSE 358 : 0.06110641 

nnet 358 : -0.3449789 
nnet mean 358 : -0.3975272 
nnet RMSE 358 : 0.1501070 


s: 359 
logit 359 : -0.4808772 
logit mean 359 : -0.467773 
logit RMSE 359 : 0.08520645 

boosting 359 : -0.7451018 
boosting mean 359 : -0.4659225 
boosting RMSE 359 : 0.1586144 

forest 359 : -0.3810044 
forest mean 359 : -0.4162228 
forest RMSE 359 : 0.06102948 

nnet 359 : -0.5443298 
nnet mean 359 : -0.3979362 
nnet RMSE 359 : 0.1500912 


s: 360 
logit 360 : -0.4483966 
logit mean 360 : -0.4677192 
logit RMSE 360 : 0.08512625 

boosting 360 : -0.4187637 
boosting mean 360 : -0.4657915 
boosting RMSE 360 : 0.158397 

forest 360 : -0.4929391 
forest mean 360 : -0.4164359 
forest RMSE 360 : 0.06114119 

nnet 360 : -0.5020364 
nnet mean 360 : -0.3982253 
nnet RMSE 360 : 0.1499790 


s: 361 
logit 361 : -0.3709465 
logit mean 361 : -0.4674511 
logit RMSE 361 : 0.08502202 

boosting 361 : -0.4008752 
boosting mean 361 : -0.4656116 
boosting RMSE 361 : 0.1581775 

forest 361 : -0.3484091 
forest mean 361 : -0.4162475 
forest RMSE 361 : 0.0611168 

nnet 361 : -0.3569223 
nnet mean 361 : -0.3981109 
nnet RMSE 361 : 0.1497883 


s: 362 
logit 362 : -0.4571229 
logit mean 362 : -0.4674226 
logit RMSE 362 : 0.08495757 

boosting 362 : -0.3236714 
boosting mean 362 : -0.4652195 
boosting RMSE 362 : 0.1580098 

forest 362 : -0.4781183 
forest mean 362 : -0.4164184 
forest RMSE 362 : 0.06117027 

nnet 362 : -0.58839 
nnet mean 362 : -0.3986365 
nnet RMSE 362 : 0.1499086 


s: 363 
logit 363 : -0.4351759 
logit mean 363 : -0.4673338 
logit RMSE 363 : 0.08486056 

boosting 363 : -0.3203326 
boosting mean 363 : -0.4648204 
boosting RMSE 363 : 0.1578474 

forest 363 : -0.3985889 
forest mean 363 : -0.4163693 
forest RMSE 363 : 0.061086 

nnet 363 : -0.2031162 
nnet mean 363 : -0.3980979 
nnet RMSE 363 : 0.1500583 


s: 364 
logit 364 : -0.4905221 
logit mean 364 : -0.4673975 
logit RMSE 364 : 0.08487663 

boosting 364 : -0.3008228 
boosting mean 364 : -0.4643699 
boosting RMSE 364 : 0.1577161 

forest 364 : -0.4317505 
forest mean 364 : -0.4164115 
forest RMSE 364 : 0.06102473 

nnet 364 : -0.6236745 
nnet mean 364 : -0.3987176 
nnet RMSE 364 : 0.1503099 


s: 365 
logit 365 : -0.4825477 
logit mean 365 : -0.467439 
logit RMSE 365 : 0.08487033 

boosting 365 : -0.4658924 
boosting mean 365 : -0.464374 
boosting RMSE 365 : 0.1575377 

forest 365 : -0.3319975 
forest mean 365 : -0.4161803 
forest RMSE 365 : 0.06104494 

nnet 365 : -0.1984679 
nnet mean 365 : -0.398169 
nnet RMSE 365 : 0.1504740 


s: 366 
logit 366 : -0.4671505 
logit mean 366 : -0.4674382 
logit RMSE 366 : 0.08482696 

boosting 366 : -0.6126819 
boosting mean 366 : -0.4647792 
boosting RMSE 366 : 0.1577146 

forest 366 : -0.4589303 
forest mean 366 : -0.4162971 
forest RMSE 366 : 0.06103926 

nnet 366 : -0.431488 
nnet mean 366 : -0.3982600 
nnet RMSE 366 : 0.1502774 


s: 367 
logit 367 : -0.4355846 
logit mean 367 : -0.4673514 
logit RMSE 367 : 0.08473168 

boosting 367 : -0.5559133 
boosting mean 367 : -0.4650276 
boosting RMSE 367 : 0.1577097 

forest 367 : -0.5065221 
forest mean 367 : -0.4165429 
forest RMSE 367 : 0.06120913 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 367 : -0.2441725 
nnet mean 367 : -0.3978402 
nnet RMSE 367 : 0.1502928 


s: 368 
logit 368 : -0.5181051 
logit mean 368 : -0.4674893 
logit RMSE 368 : 0.08484016 

boosting 368 : -0.7489475 
boosting mean 368 : -0.4657991 
boosting RMSE 368 : 0.1585423 

forest 368 : -0.5184467 
forest mean 368 : -0.4168198 
forest RMSE 368 : 0.06143696 

nnet 368 : -0.485875 
nnet mean 368 : -0.3980794 
nnet RMSE 368 : 0.1501552 


s: 369 
logit 369 : -0.4915333 
logit mean 369 : -0.4675545 
logit RMSE 369 : 0.084859 

boosting 369 : -0.2933109 
boosting mean 369 : -0.4653316 
boosting RMSE 369 : 0.1584247 

forest 369 : -0.3923029 
forest mean 369 : -0.4167534 
forest RMSE 369 : 0.06135497 

nnet 369 : -0.3078592 
nnet mean 369 : -0.3978349 
nnet RMSE 369 : 0.1500283 


s: 370 
logit 370 : -0.371637 
logit mean 370 : -0.4672952 
logit RMSE 370 : 0.08475708 

boosting 370 : -0.3508478 
boosting mean 370 : -0.4650222 
boosting RMSE 370 : 0.1582311 

forest 370 : -0.343546 
forest mean 370 : -0.4165555 
forest RMSE 370 : 0.06134225 

nnet 370 : -0.2701359 
nnet mean 370 : -0.3974898 
nnet RMSE 370 : 0.1499774 


s: 371 
logit 371 : -0.4256287 
logit mean 371 : -0.4671829 
logit RMSE 371 : 0.08465324 

boosting 371 : -0.495662 
boosting mean 371 : -0.4651048 
boosting RMSE 371 : 0.1580957 

forest 371 : -0.4469567 
forest mean 371 : -0.4166375 
forest RMSE 371 : 0.06130801 

nnet 371 : -0.4123726 
nnet mean 371 : -0.3975299 
nnet RMSE 371 : 0.1497765 


s: 372 
logit 372 : -0.3938024 
logit mean 372 : -0.4669857 
logit RMSE 372 : 0.08453999 

boosting 372 : -0.5000036 
boosting mean 372 : -0.4651986 
boosting RMSE 372 : 0.1579682 

forest 372 : -0.4442414 
forest mean 372 : -0.4167117 
forest RMSE 372 : 0.0612685 

nnet 372 : -0.4242744 
nnet mean 372 : -0.3976018 
nnet RMSE 372 : 0.1495804 


s: 373 
logit 373 : -0.5114855 
logit mean 373 : -0.467105 
logit RMSE 373 : 0.0846237 

boosting 373 : -0.4824791 
boosting mean 373 : -0.4652449 
boosting RMSE 373 : 0.1578141 

forest 373 : -0.448766 
forest mean 373 : -0.4167976 
forest RMSE 373 : 0.0612384 

nnet 373 : -0.4512904 
nnet mean 373 : -0.3977457 
nnet RMSE 373 : 0.1494033 


s: 374 
logit 374 : -0.5156755 
logit mean 374 : -0.4672348 
logit RMSE 374 : 0.0847219 

boosting 374 : -0.2319765 
boosting mean 374 : -0.4646212 
boosting RMSE 374 : 0.1578423 

forest 374 : -0.4567288 
forest mean 374 : -0.4169044 
forest RMSE 374 : 0.06122678 

nnet 374 : -0.2052203 
nnet mean 374 : -0.3972310 
nnet RMSE 374 : 0.1495430 


s: 375 
logit 375 : -0.4091482 
logit mean 375 : -0.4670799 
logit RMSE 375 : 0.08461018 

boosting 375 : -0.4002375 
boosting mean 375 : -0.4644495 
boosting RMSE 375 : 0.1576317 

forest 375 : -0.3308488 
forest mean 375 : -0.4166749 
forest RMSE 375 : 0.06124928 

nnet 375 : -0.3794747 
nnet mean 375 : -0.3971836 
nnet RMSE 375 : 0.1493473 


s: 376 
logit 376 : -0.5206521 
logit mean 376 : -0.4672224 
logit RMSE 376 : 0.08472638 

boosting 376 : -0.2184943 
boosting mean 376 : -0.4637954 
boosting RMSE 376 : 0.1577000 

forest 376 : -0.3247017 
forest mean 376 : -0.4164303 
forest RMSE 376 : 0.06129091 

nnet 376 : -0.4110242 
nnet mean 376 : -0.3972204 
nnet RMSE 376 : 0.1491496 


s: 377 
logit 377 : -0.4107436 
logit mean 377 : -0.4670726 
logit RMSE 377 : 0.08461574 

boosting 377 : -0.2522087 
boosting mean 377 : -0.4632342 
boosting RMSE 377 : 0.1576745 

forest 377 : -0.4104576 
forest mean 377 : -0.4164144 
forest RMSE 377 : 0.06121194 

nnet 377 : -0.2842416 
nnet mean 377 : -0.3969207 
nnet RMSE 377 : 0.1490709 


s: 378 
logit 378 : -0.4486472 
logit mean 378 : -0.4670239 
logit RMSE 378 : 0.08454078 

boosting 378 : -0.3744369 
boosting mean 378 : -0.4629993 
boosting RMSE 378 : 0.1574713 

forest 378 : -0.4164839 
forest mean 378 : -0.4164146 
forest RMSE 378 : 0.0611368 

nnet 378 : -0.465469 
nnet mean 378 : -0.3971021 
nnet RMSE 378 : 0.1489117 


s: 379 
logit 379 : -0.5172022 
logit mean 379 : -0.4671563 
logit RMSE 379 : 0.08464354 

boosting 379 : -0.2759827 
boosting mean 379 : -0.4625058 
boosting RMSE 379 : 0.1573924 

forest 379 : -0.4242402 
forest mean 379 : -0.4164353 
forest RMSE 379 : 0.06106879 

nnet 379 : -0.3047966 
nnet mean 379 : -0.3968585 
nnet RMSE 379 : 0.1487955 


s: 380 
logit 380 : -0.3849815 
logit mean 380 : -0.46694 
logit RMSE 380 : 0.0845356 

boosting 380 : -0.2465674 
boosting mean 380 : -0.4619376 
boosting RMSE 380 : 0.1573821 

forest 380 : -0.4355262 
forest mean 380 : -0.4164855 
forest RMSE 380 : 0.0610156 

nnet 380 : -0.6384542 
nnet mean 380 : -0.3974943 
nnet RMSE 380 : 0.1491022 


s: 381 
logit 381 : -0.4149602 
logit mean 381 : -0.4668036 
logit RMSE 381 : 0.08442807 

boosting 381 : -0.5211562 
boosting mean 381 : -0.462093 
boosting RMSE 381 : 0.1572979 

forest 381 : -0.4279142 
forest mean 381 : -0.4165155 
forest RMSE 381 : 0.06095226 

nnet 381 : -0.2751116 
nnet mean 381 : -0.3971731 
nnet RMSE 381 : 0.1490438 


s: 382 
logit 382 : -0.4747623 
logit mean 382 : -0.4668244 
logit RMSE 382 : 0.08440421 

boosting 382 : -0.2821828 
boosting mean 382 : -0.461622 
boosting RMSE 382 : 0.1572075 

forest 382 : -0.4032998 
forest mean 382 : -0.4164809 
forest RMSE 382 : 0.06087266 

nnet 382 : -0.4710026 
nnet mean 382 : -0.3973664 
nnet RMSE 382 : 0.1488929 


s: 383 
logit 383 : -0.4379633 
logit mean 383 : -0.4667491 
logit RMSE 383 : 0.08431627 

boosting 383 : -0.3984256 
boosting mean 383 : -0.461457 
boosting RMSE 383 : 0.1570022 

forest 383 : -0.3526303 
forest mean 383 : -0.4163142 
forest RMSE 383 : 0.0608413 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 383 : -0.2194964 
nnet mean 383 : -0.3969020 
nnet RMSE 383 : 0.1489842 


s: 384 
logit 384 : -0.4737073 
logit mean 384 : -0.4667672 
logit RMSE 384 : 0.08429038 

boosting 384 : -0.3996934 
boosting mean 384 : -0.4612962 
boosting RMSE 384 : 0.1567976 

forest 384 : -0.3457376 
forest mean 384 : -0.4161304 
forest RMSE 384 : 0.0608251 

nnet 384 : -0.4029269 
nnet mean 384 : -0.3969176 
nnet RMSE 384 : 0.1487901 


s: 385 
logit 385 : -0.5186586 
logit mean 385 : -0.466902 
logit RMSE 385 : 0.08439778 

boosting 385 : -0.5336454 
boosting mean 385 : -0.4614841 
boosting RMSE 385 : 0.1567419 

forest 385 : -0.4481066 
forest mean 385 : -0.4162135 
forest RMSE 385 : 0.06079551 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 385 : -0.237499 
nnet mean 385 : -0.3965036 
nnet RMSE 385 : 0.1488274 


s: 386 
logit 386 : -0.4223919 
logit mean 386 : -0.4667867 
logit RMSE 386 : 0.08429609 

boosting 386 : -0.2840688 
boosting mean 386 : -0.4610245 
boosting RMSE 386 : 0.1566499 

forest 386 : -0.4260922 
forest mean 386 : -0.4162391 
forest RMSE 386 : 0.06073123 

nnet 386 : -0.618934 
nnet mean 386 : -0.3970798 
nnet RMSE 386 : 0.1490516 


s: 387 
logit 387 : -0.5127107 
logit mean 387 : -0.4669053 
logit RMSE 387 : 0.08438184 

boosting 387 : -0.1621141 
boosting mean 387 : -0.4602521 
boosting RMSE 387 : 0.1569140 

forest 387 : -0.4027191 
forest mean 387 : -0.4162041 
forest RMSE 387 : 0.06065287 

nnet 387 : -0.1458171 
nnet mean 387 : -0.3964306 
nnet RMSE 387 : 0.1494186 


s: 388 
logit 388 : -0.476202 
logit mean 388 : -0.4669293 
logit RMSE 388 : 0.08436178 

boosting 388 : -0.2836003 
boosting mean 388 : -0.4597968 
boosting RMSE 388 : 0.1568231 

forest 388 : -0.4051589 
forest mean 388 : -0.4161757 
forest RMSE 388 : 0.06057523 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 388 : -0.318413 
nnet mean 388 : -0.3962295 
nnet RMSE 388 : 0.1492834 


s: 389 
logit 389 : -0.4521645 
logit mean 389 : -0.4668913 
logit RMSE 389 : 0.08429478 

boosting 389 : -0.138692 
boosting mean 389 : -0.4589713 
boosting RMSE 389 : 0.1571807 

forest 389 : -0.5037734 
forest mean 389 : -0.4164008 
forest RMSE 389 : 0.06072568 

nnet 389 : -0.5455337 
nnet mean 389 : -0.3966133 
nnet RMSE 389 : 0.1492739 


s: 390 
logit 390 : -0.4567251 
logit mean 390 : -0.4668653 
logit RMSE 390 : 0.08423562 

boosting 390 : -0.6119777 
boosting mean 390 : -0.4593637 
boosting RMSE 390 : 0.1573456 

forest 390 : -0.3990829 
forest mean 390 : -0.4163564 
forest RMSE 390 : 0.0606478 

nnet 390 : -0.2740755 
nnet mean 390 : -0.3962991 
nnet RMSE 390 : 0.1492187 


s: 391 
logit 391 : -0.4843824 
logit mean 391 : -0.4669101 
logit RMSE 391 : 0.084236 

boosting 391 : -0.3866111 
boosting mean 391 : -0.4591776 
boosting RMSE 391 : 0.1571458 

forest 391 : -0.3478112 
forest mean 391 : -0.4161811 
forest RMSE 391 : 0.06062767 

nnet 391 : -0.3324044 
nnet mean 391 : -0.3961357 
nnet RMSE 391 : 0.1490670 


s: 392 
logit 392 : -0.5617097 
logit mean 392 : -0.4671519 
logit RMSE 392 : 0.08452403 

boosting 392 : -0.503249 
boosting mean 392 : -0.45929 
boosting RMSE 392 : 0.1570318 

forest 392 : -0.4475746 
forest mean 392 : -0.4162612 
forest RMSE 392 : 0.06059795 

nnet 392 : -0.5263584 
nnet mean 392 : -0.3964679 
nnet RMSE 392 : 0.1490135 


s: 393 
logit 393 : -0.5501564 
logit mean 393 : -0.4673631 
logit RMSE 393 : 0.08475555 

boosting 393 : -0.4331947 
boosting mean 393 : -0.4592236 
boosting RMSE 393 : 0.1568408 

forest 393 : -0.3750887 
forest mean 393 : -0.4161564 
forest RMSE 393 : 0.06053385 

nnet 393 : -0.2004878 
nnet mean 393 : -0.3959692 
nnet RMSE 393 : 0.1491636 


s: 394 
logit 394 : -0.4544848 
logit mean 394 : -0.4673304 
logit RMSE 394 : 0.08469242 

boosting 394 : -0.3977406 
boosting mean 394 : -0.4590676 
boosting RMSE 394 : 0.1566417 

forest 394 : -0.5012686 
forest mean 394 : -0.4163725 
forest RMSE 394 : 0.06067186 

nnet 394 : -0.3321991 
nnet mean 394 : -0.3958074 
nnet RMSE 394 : 0.1490134 


s: 395 
logit 395 : -0.4465345 
logit mean 395 : -0.4672778 
logit RMSE 395 : 0.08461755 

boosting 395 : -0.4454242 
boosting mean 395 : -0.459033 
boosting RMSE 395 : 0.15646 

forest 395 : -0.4679843 
forest mean 395 : -0.4165031 
forest RMSE 395 : 0.06069149 

nnet 395 : -0.7615042 
nnet mean 395 : -0.3967332 
nnet RMSE 395 : 0.1499321 


s: 396 
logit 396 : -0.5784763 
logit mean 396 : -0.4675586 
logit RMSE 396 : 0.08498522 

boosting 396 : -0.5845012 
boosting mean 396 : -0.4593499 
boosting RMSE 396 : 0.1565371 

forest 396 : -0.4276156 
forest mean 396 : -0.4165312 
forest RMSE 396 : 0.06063069 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 396 : -0.2539439 
nnet mean 396 : -0.3963726 
nnet RMSE 396 : 0.1499224 


s: 397 
logit 397 : -0.4931776 
logit mean 397 : -0.4676231 
logit RMSE 397 : 0.08500685 

boosting 397 : -0.5641783 
boosting mean 397 : -0.4596139 
boosting RMSE 397 : 0.1565569 

forest 397 : -0.4343811 
forest mean 397 : -0.4165762 
forest RMSE 397 : 0.06057886 

nnet 397 : -0.7584362 
nnet mean 397 : -0.3972846 
nnet RMSE 397 : 0.1508102 


s: 398 
logit 398 : -0.4913382 
logit mean 398 : -0.4676827 
logit RMSE 398 : 0.08502334 

boosting 398 : -0.6062663 
boosting mean 398 : -0.4599824 
boosting RMSE 398 : 0.1567015 

forest 398 : -0.45582 
forest mean 398 : -0.4166748 
forest RMSE 398 : 0.06056738 

nnet 398 : -0.5202425 
nnet mean 398 : -0.3975935 
nnet RMSE 398 : 0.1507412 


s: 399 
logit 399 : -0.4264018 
logit mean 399 : -0.4675792 
logit RMSE 399 : 0.08492702 

boosting 399 : -0.6587193 
boosting mean 399 : -0.4604805 
boosting RMSE 399 : 0.1570401 

forest 399 : -0.5475412 
forest mean 399 : -0.4170027 
forest RMSE 399 : 0.06094071 

nnet 399 : -0.3988501 
nnet mean 399 : -0.3975967 
nnet RMSE 399 : 0.1505522 


s: 400 
logit 400 : -0.4850179 
logit mean 400 : -0.4676228 
logit RMSE 400 : 0.08492724 

boosting 400 : -0.5238097 
boosting mean 400 : -0.4606388 
boosting RMSE 400 : 0.1569658 

forest 400 : -0.4782253 
forest mean 400 : -0.4171558 
forest RMSE 400 : 0.06099003 

nnet 400 : -0.4477236 
nnet mean 400 : -0.397722 
nnet RMSE 400 : 0.1503828 


s: 401 
logit 401 : -0.4895750 
logit mean 401 : -0.4676776 
logit RMSE 401 : 0.08493915 

boosting 401 : -0.5697417 
boosting mean 401 : -0.4609109 
boosting RMSE 401 : 0.1569989 

forest 401 : -0.4203734 
forest mean 401 : -0.4171638 
forest RMSE 401 : 0.06092243 

nnet 401 : -0.4189693 
nnet mean 401 : -0.397775 
nnet RMSE 401 : 0.1501982 


s: 402 
logit 402 : -0.482481 
logit mean 402 : -0.4677144 
logit RMSE 402 : 0.08493313 

boosting 402 : -0.3194219 
boosting mean 402 : -0.4605589 
boosting RMSE 402 : 0.156855 

forest 402 : -0.4830426 
forest mean 402 : -0.4173277 
forest RMSE 402 : 0.06098741 

nnet 402 : -0.2033996 
nnet mean 402 : -0.3972915 
nnet RMSE 402 : 0.1503314 


s: 403 
logit 403 : -0.3971857 
logit mean 403 : -0.4675394 
logit RMSE 403 : 0.0848278 

boosting 403 : -0.466389 
boosting mean 403 : -0.4605734 
boosting RMSE 403 : 0.1566952 

forest 403 : -0.3928064 
forest mean 403 : -0.4172669 
forest RMSE 403 : 0.06091275 

nnet 403 : -0.6790168 
nnet mean 403 : -0.3979905 
nnet RMSE 403 : 0.1507867 


s: 404 
logit 404 : -0.5353413 
logit mean 404 : -0.4677072 
logit RMSE 404 : 0.0849899 

boosting 404 : -0.4413657 
boosting mean 404 : -0.4605258 
boosting RMSE 404 : 0.1565147 

forest 404 : -0.4390283 
forest mean 404 : -0.4173207 
forest RMSE 404 : 0.0608683 

nnet 404 : -0.3576684 
nnet mean 404 : -0.3978907 
nnet RMSE 404 : 0.1506147 


s: 405 
logit 405 : -0.4341166 
logit mean 405 : -0.4676243 
logit RMSE 405 : 0.08490184 

boosting 405 : -0.4730918 
boosting mean 405 : -0.4605569 
boosting RMSE 405 : 0.1563635 

forest 405 : -0.3928201 
forest mean 405 : -0.4172602 
forest RMSE 405 : 0.06079415 

nnet 405 : -0.4136163 
nnet mean 405 : -0.3979295 
nnet RMSE 405 : 0.1504301 


s: 406 
logit 406 : -0.4532487 
logit mean 406 : -0.4675889 
logit RMSE 406 : 0.08483839 

boosting 406 : -0.312922 
boosting mean 406 : -0.4601932 
boosting RMSE 406 : 0.1562306 

forest 406 : -0.3804333 
forest mean 406 : -0.4171695 
forest RMSE 406 : 0.060727 

nnet 406 : -0.4199951 
nnet mean 406 : -0.3979839 
nnet RMSE 406 : 0.1502480 


s: 407 
logit 407 : -0.4746674 
logit mean 407 : -0.4676063 
logit RMSE 407 : 0.0848149 

boosting 407 : -0.3394847 
boosting mean 407 : -0.4598967 
boosting RMSE 407 : 0.1560674 

forest 407 : -0.4434417 
forest mean 407 : -0.4172341 
forest RMSE 407 : 0.06069057 

nnet 407 : -0.3909763 
nnet mean 407 : -0.3979667 
nnet RMSE 407 : 0.150064 


s: 408 
logit 408 : -0.3971539 
logit mean 408 : -0.4674336 
logit RMSE 408 : 0.084711 

boosting 408 : -0.4534308 
boosting mean 408 : -0.4598808 
boosting RMSE 408 : 0.1558985 

forest 408 : -0.5172126 
forest mean 408 : -0.4174791 
forest RMSE 408 : 0.06089327 

nnet 408 : -0.3949275 
nnet mean 408 : -0.3979592 
nnet RMSE 408 : 0.1498802 


s: 409 
logit 409 : -0.3735377 
logit mean 409 : -0.467204 
logit RMSE 409 : 0.0846175 

boosting 409 : -0.4747895 
boosting mean 409 : -0.4599173 
boosting RMSE 409 : 0.1557517 

forest 409 : -0.3495303 
forest mean 409 : -0.417313 
forest RMSE 409 : 0.06086996 

nnet 409 : -0.2337960 
nnet mean 409 : -0.3975579 
nnet RMSE 409 : 0.1499223 


s: 410 
logit 410 : -0.4263531 
logit mean 410 : -0.4671044 
logit RMSE 410 : 0.08452427 

boosting 410 : -0.4553393 
boosting mean 410 : -0.4599061 
boosting RMSE 410 : 0.1555856 

forest 410 : -0.3666963 
forest mean 410 : -0.4171895 
forest RMSE 410 : 0.06081793 

nnet 410 : -0.4479423 
nnet mean 410 : -0.3976807 
nnet RMSE 410 : 0.1497581 


s: 411 
logit 411 : -0.4755357 
logit mean 411 : -0.4671249 
logit RMSE 411 : 0.08450356 

boosting 411 : -0.4441669 
boosting mean 411 : -0.4598678 
boosting RMSE 411 : 0.1554115 

forest 411 : -0.446305 
forest mean 411 : -0.4172604 
forest RMSE 411 : 0.06078682 

nnet 411 : -0.6173451 
nnet mean 411 : -0.3982152 
nnet RMSE 411 : 0.1499595 


s: 412 
logit 412 : -0.3939376 
logit mean 412 : -0.4669472 
logit RMSE 412 : 0.08440147 

boosting 412 : -0.4728826 
boosting mean 412 : -0.4598994 
boosting RMSE 412 : 0.1552643 

forest 412 : -0.3801212 
forest mean 412 : -0.4171702 
forest RMSE 412 : 0.06072091 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 412 : -0.1889929 
nnet mean 412 : -0.3977074 
nnet RMSE 412 : 0.1501377 


s: 413 
logit 413 : -0.4666901 
logit mean 413 : -0.4669466 
logit RMSE 413 : 0.08436308 

boosting 413 : -0.5617115 
boosting mean 413 : -0.4601459 
boosting RMSE 413 : 0.1552802 

forest 413 : -0.4544920 
forest mean 413 : -0.4172606 
forest RMSE 413 : 0.0607066 

nnet 413 : -0.2351501 
nnet mean 413 : -0.3973138 
nnet RMSE 413 : 0.1501751 


s: 414 
logit 414 : -0.4205019 
logit mean 414 : -0.4668344 
logit RMSE 414 : 0.08426715 

boosting 414 : -0.5454836 
boosting mean 414 : -0.460352 
boosting RMSE 414 : 0.1552573 

forest 414 : -0.4452788 
forest mean 414 : -0.4173283 
forest RMSE 414 : 0.06067406 

nnet 414 : -0.4741858 
nnet mean 414 : -0.3974995 
nnet RMSE 414 : 0.1500379 


s: 415 
logit 415 : -0.5083648 
logit mean 415 : -0.4669345 
logit RMSE 415 : 0.0843335 

boosting 415 : -0.6039505 
boosting mean 415 : -0.4606981 
boosting RMSE 415 : 0.1553930 

forest 415 : -0.4638639 
forest mean 415 : -0.4174404 
forest RMSE 415 : 0.06068195 

nnet 415 : -0.3274034 
nnet mean 415 : -0.3973306 
nnet RMSE 415 : 0.1498994 


s: 416 
logit 416 : -0.4703972 
logit mean 416 : -0.4669428 
logit RMSE 416 : 0.08430276 

boosting 416 : -0.4999039 
boosting mean 416 : -0.4607923 
boosting RMSE 416 : 0.1552834 

forest 416 : -0.4022021 
forest mean 416 : -0.4174038 
forest RMSE 416 : 0.06060906 

nnet 416 : -0.4439707 
nnet mean 416 : -0.3974427 
nnet RMSE 416 : 0.1497346 


s: 417 
logit 417 : -0.4443977 
logit mean 417 : -0.4668888 
logit RMSE 417 : 0.08422968 

boosting 417 : -0.4148805 
boosting mean 417 : -0.4606822 
boosting RMSE 417 : 0.1550988 

forest 417 : -0.3588684 
forest mean 417 : -0.4172634 
forest RMSE 417 : 0.06056985 

nnet 417 : -0.2797993 
nnet mean 417 : -0.3971606 
nnet RMSE 417 : 0.1496708 


s: 418 
logit 418 : -0.5396762 
logit mean 418 : -0.4670629 
logit RMSE 418 : 0.0844058 

boosting 418 : -0.6675773 
boosting mean 418 : -0.4611772 
boosting RMSE 418 : 0.155465 

forest 418 : -0.4773915 
forest mean 418 : -0.4174072 
forest RMSE 418 : 0.06061566 

nnet 418 : -0.3884345 
nnet mean 418 : -0.3971397 
nnet RMSE 418 : 0.1494927 


s: 419 
logit 419 : -0.5900288 
logit mean 419 : -0.4673564 
logit RMSE 419 : 0.08481462 

boosting 419 : -0.5071527 
boosting mean 419 : -0.4612869 
boosting RMSE 419 : 0.1553676 

forest 419 : -0.3779482 
forest mean 419 : -0.4173131 
forest RMSE 419 : 0.06055287 

nnet 419 : -0.4401834 
nnet mean 419 : -0.3972424 
nnet RMSE 419 : 0.1493271 


s: 420 
logit 420 : -0.4095946 
logit mean 420 : -0.4672188 
logit RMSE 420 : 0.08471488 

boosting 420 : -0.5190219 
boosting mean 420 : -0.4614244 
boosting RMSE 420 : 0.1552912 

forest 420 : -0.4822047 
forest mean 420 : -0.4174676 
forest RMSE 420 : 0.0606136 

nnet 420 : -0.6177023 
nnet mean 420 : -0.3977673 
nnet RMSE 420 : 0.1495270 


s: 421 
logit 421 : -0.4705097 
logit mean 421 : -0.4672267 
logit RMSE 421 : 0.08468396 

boosting 421 : -0.2870853 
boosting mean 421 : -0.4610102 
boosting RMSE 421 : 0.1552042 

forest 421 : -0.3948758 
forest mean 421 : -0.4174139 
forest RMSE 421 : 0.06054209 

nnet 421 : -0.3624582 
nnet mean 421 : -0.3976834 
nnet RMSE 421 : 0.1493606 


s: 422 
logit 422 : -0.4441768 
logit mean 422 : -0.467172 
logit RMSE 422 : 0.0846109 

boosting 422 : -0.5051761 
boosting mean 422 : -0.4611149 
boosting RMSE 422 : 0.1551047 

forest 422 : -0.4097902 
forest mean 422 : -0.4173958 
forest RMSE 422 : 0.06047219 

nnet 422 : -0.5832471 
nnet mean 422 : -0.3981232 
nnet RMSE 422 : 0.1494499 


s: 423 
logit 423 : -0.3614717 
logit mean 423 : -0.4669222 
logit RMSE 423 : 0.08453159 

boosting 423 : -0.5279441 
boosting mean 423 : -0.4612729 
boosting RMSE 423 : 0.1550461 

forest 423 : -0.399766 
forest mean 423 : -0.4173542 
forest RMSE 423 : 0.06040067 

nnet 423 : -0.44516 
nnet mean 423 : -0.3982344 
nnet RMSE 423 : 0.1492893 


s: 424 
logit 424 : -0.5271722 
logit mean 424 : -0.4670643 
logit RMSE 424 : 0.08465743 

boosting 424 : -0.6149025 
boosting mean 424 : -0.4616352 
boosting RMSE 424 : 0.1552145 

forest 424 : -0.4752131 
forest mean 424 : -0.4174906 
forest RMSE 424 : 0.06043988 

nnet 424 : -0.5265606 
nnet mean 424 : -0.398537 
nnet RMSE 424 : 0.1492398 


s: 425 
logit 425 : -0.5226303 
logit mean 425 : -0.467195 
logit RMSE 425 : 0.08476674 

boosting 425 : -0.5990314 
boosting mean 425 : -0.4619585 
boosting RMSE 425 : 0.1553321 

forest 425 : -0.4391085 
forest mean 425 : -0.4175415 
forest RMSE 425 : 0.06039853 

nnet 425 : -0.3476422 
nnet mean 425 : -0.3984173 
nnet RMSE 425 : 0.1490858 


s: 426 
logit 426 : -0.553065 
logit mean 426 : -0.4673966 
logit RMSE 426 : 0.08499136 

boosting 426 : -0.6051813 
boosting mean 426 : -0.4622947 
boosting RMSE 426 : 0.1554678 

forest 426 : -0.4632930 
forest mean 426 : -0.4176489 
forest RMSE 426 : 0.06040549 

nnet 426 : -0.3579748 
nnet mean 426 : -0.3983223 
nnet RMSE 426 : 0.1489246 


s: 427 
logit 427 : -0.5312065 
logit mean 427 : -0.467546 
logit RMSE 427 : 0.0851289 

boosting 427 : -0.1529168 
boosting mean 427 : -0.4615702 
boosting RMSE 427 : 0.1557453 

forest 427 : -0.3497943 
forest mean 427 : -0.41749 
forest RMSE 427 : 0.06038361 

nnet 427 : -0.4671794 
nnet mean 427 : -0.3984836 
nnet RMSE 427 : 0.1487856 


s: 428 
logit 428 : -0.5096577 
logit mean 428 : -0.4676444 
logit RMSE 428 : 0.08519445 

boosting 428 : -0.4127816 
boosting mean 428 : -0.4614562 
boosting RMSE 428 : 0.1555645 

forest 428 : -0.3330873 
forest mean 428 : -0.4172928 
forest RMSE 428 : 0.06039969 

nnet 428 : -0.2110553 
nnet mean 428 : -0.3980457 
nnet RMSE 428 : 0.1488921 


s: 429 
logit 429 : -0.5816132 
logit mean 429 : -0.4679101 
logit RMSE 429 : 0.08554566 

boosting 429 : -0.6087584 
boosting mean 429 : -0.4617995 
boosting RMSE 429 : 0.1557096 

forest 429 : -0.4894422 
forest mean 429 : -0.4174610 
forest RMSE 429 : 0.0604836 

nnet 429 : -0.5990098 
nnet mean 429 : -0.3985141 
nnet RMSE 429 : 0.1490285 


s: 430 
logit 430 : -0.4258886 
logit mean 430 : -0.4678123 
logit RMSE 430 : 0.08545525 

boosting 430 : -0.3045241 
boosting mean 430 : -0.4614338 
boosting RMSE 430 : 0.1555966 

forest 430 : -0.4078246 
forest mean 430 : -0.4174385 
forest RMSE 430 : 0.06041441 

nnet 430 : -0.4639664 
nnet mean 430 : -0.3986663 
nnet RMSE 430 : 0.1488871 


s: 431 
logit 431 : -0.447795 
logit mean 431 : -0.4677659 
logit RMSE 431 : 0.0853871 

boosting 431 : -0.8854494 
boosting mean 431 : -0.4624176 
boosting RMSE 431 : 0.1571652 

forest 431 : -0.3881794 
forest mean 431 : -0.4173707 
forest RMSE 431 : 0.06034697 

nnet 431 : -0.4510619 
nnet mean 431 : -0.3987879 
nnet RMSE 431 : 0.1487346 


s: 432 
logit 432 : -0.3859179 
logit mean 432 : -0.4675764 
logit RMSE 432 : 0.0852909 

boosting 432 : -0.5241831 
boosting mean 432 : -0.4625606 
boosting RMSE 432 : 0.1570969 

forest 432 : -0.3914007 
forest mean 432 : -0.4173105 
forest RMSE 432 : 0.0602785 

nnet 432 : -0.3288690 
nnet mean 432 : -0.3986261 
nnet RMSE 432 : 0.1486018 


s: 433 
logit 433 : -0.4605586 
logit mean 433 : -0.4675602 
logit RMSE 433 : 0.08524205 

boosting 433 : -0.88328 
boosting mean 433 : -0.4635322 
boosting RMSE 433 : 0.1586248 

forest 433 : -0.5211859 
forest mean 433 : -0.4175504 
forest RMSE 433 : 0.06048986 

nnet 433 : -0.2684880 
nnet mean 433 : -0.3983255 
nnet RMSE 433 : 0.1485646 


s: 434 
logit 434 : -0.3993866 
logit mean 434 : -0.4674031 
logit RMSE 434 : 0.0851438 

boosting 434 : -0.5995701 
boosting mean 434 : -0.4638457 
boosting RMSE 434 : 0.1587313 

forest 434 : -0.4036076 
forest mean 434 : -0.4175183 
forest RMSE 434 : 0.06042038 

nnet 434 : -0.4432323 
nnet mean 434 : -0.398429 
nnet RMSE 434 : 0.1484078 


s: 435 
logit 435 : -0.480901 
logit mean 435 : -0.4674342 
logit RMSE 435 : 0.08513428 

boosting 435 : -0.2876656 
boosting mean 435 : -0.4634406 
boosting RMSE 435 : 0.1586402 

forest 435 : -0.3877451 
forest mean 435 : -0.4174499 
forest RMSE 435 : 0.06035375 

nnet 435 : -0.2917969 
nnet mean 435 : -0.3981838 
nnet RMSE 435 : 0.1483279 


s: 436 
logit 436 : -0.5067296 
logit mean 436 : -0.4675243 
logit RMSE 436 : 0.08519008 

boosting 436 : -0.471343 
boosting mean 436 : -0.4634588 
boosting RMSE 436 : 0.158495 

forest 436 : -0.3942391 
forest mean 436 : -0.4173966 
forest RMSE 436 : 0.06028513 

nnet 436 : -0.3937794 
nnet mean 436 : -0.3981737 
nnet RMSE 436 : 0.1481580 


s: 437 
logit 437 : -0.4157288 
logit mean 437 : -0.4674058 
logit RMSE 437 : 0.08509588 

boosting 437 : -0.2951140 
boosting mean 437 : -0.4630735 
boosting RMSE 437 : 0.1583930 

forest 437 : -0.4139429 
forest mean 437 : -0.4173887 
forest RMSE 437 : 0.06021981 

nnet 437 : -0.6555135 
nnet mean 437 : -0.3987626 
nnet RMSE 437 : 0.1484923 


s: 438 
logit 438 : -0.4157289 
logit mean 438 : -0.4672878 
logit RMSE 438 : 0.085002 

boosting 438 : -0.4957512 
boosting mean 438 : -0.4631481 
boosting RMSE 438 : 0.1582783 

forest 438 : -0.3724413 
forest mean 438 : -0.4172861 
forest RMSE 438 : 0.06016544 

nnet 438 : -0.2913879 
nnet mean 438 : -0.3985175 
nnet RMSE 438 : 0.1484134 


s: 439 
logit 439 : -0.4313612 
logit mean 439 : -0.467206 
logit RMSE 439 : 0.08491833 

boosting 439 : -0.462734 
boosting mean 439 : -0.4631472 
boosting RMSE 439 : 0.1581262 

forest 439 : -0.4235323 
forest mean 439 : -0.4173003 
forest RMSE 439 : 0.06010737 

nnet 439 : -0.5701249 
nnet mean 439 : -0.3989084 
nnet RMSE 439 : 0.1484665 


s: 440 
logit 440 : -0.4400487 
logit mean 440 : -0.4671442 
logit RMSE 440 : 0.08484326 

boosting 440 : -0.5129452 
boosting mean 440 : -0.4632604 
boosting RMSE 440 : 0.1580382 

forest 440 : -0.3888104 
forest mean 440 : -0.4172356 
forest RMSE 440 : 0.0600414 

nnet 440 : -0.2954604 
nnet mean 440 : -0.3986733 
nnet RMSE 440 : 0.1483814 


s: 441 
logit 441 : -0.5147543 
logit mean 441 : -0.4672522 
logit RMSE 441 : 0.084923 

boosting 441 : -0.5122672 
boosting mean 441 : -0.4633715 
boosting RMSE 441 : 0.1579494 

forest 441 : -0.4803362 
forest mean 441 : -0.4173787 
forest RMSE 441 : 0.06009517 

nnet 441 : -0.545184 
nnet mean 441 : -0.3990055 
nnet RMSE 441 : 0.1483742 


s: 442 
logit 442 : -0.4339106 
logit mean 442 : -0.4671768 
logit RMSE 442 : 0.08484221 

boosting 442 : -0.4458055 
boosting mean 442 : -0.4633318 
boosting RMSE 442 : 0.1577857 

forest 442 : -0.3640197 
forest mean 442 : -0.4172580 
forest RMSE 442 : 0.06005154 

nnet 442 : -0.1266281 
nnet mean 442 : -0.3983893 
nnet RMSE 442 : 0.1487756 


s: 443 
logit 443 : -0.5214845 
logit mean 443 : -0.4672994 
logit RMSE 443 : 0.08494273 

boosting 443 : -0.2197345 
boosting mean 443 : -0.4627819 
boosting RMSE 443 : 0.1578400 

forest 443 : -0.4752916 
forest mean 443 : -0.4173890 
forest RMSE 443 : 0.0600903 

nnet 443 : -0.1588179 
nnet mean 443 : -0.3978485 
nnet RMSE 443 : 0.1490487 


s: 444 
logit 444 : -0.491383 
logit mean 444 : -0.4673536 
logit RMSE 444 : 0.08495778 

boosting 444 : -0.4948878 
boosting mean 444 : -0.4628542 
boosting RMSE 444 : 0.1577265 

forest 444 : -0.4633462 
forest mean 444 : -0.4174925 
forest RMSE 444 : 0.06009783 

nnet 444 : -0.3405189 
nnet mean 444 : -0.3977193 
nnet RMSE 444 : 0.1489075 


s: 445 
logit 445 : -0.3984232 
logit mean 445 : -0.4671987 
logit RMSE 445 : 0.0848623 

boosting 445 : -0.3997882 
boosting mean 445 : -0.4627125 
boosting RMSE 445 : 0.1575492 

forest 445 : -0.3257031 
forest mean 445 : -0.4172862 
forest RMSE 445 : 0.0601335 

nnet 445 : -0.5430816 
nnet mean 445 : -0.398046 
nnet RMSE 445 : 0.1488947 


s: 446 
logit 446 : -0.4233396 
logit mean 446 : -0.4671004 
logit RMSE 446 : 0.08477432 

boosting 446 : -0.5117784 
boosting mean 446 : -0.4628225 
boosting RMSE 446 : 0.1574614 

forest 446 : -0.4408993 
forest mean 446 : -0.4173391 
forest RMSE 446 : 0.06009726 

nnet 446 : -0.462047 
nnet mean 446 : -0.3981895 
nnet RMSE 446 : 0.1487567 


s: 447 
logit 447 : -0.5023683 
logit mean 447 : -0.4671793 
logit RMSE 447 : 0.08481775 

boosting 447 : -0.4312433 
boosting mean 447 : -0.4627518 
boosting RMSE 447 : 0.1572921 

forest 447 : -0.3750780 
forest mean 447 : -0.4172446 
forest RMSE 447 : 0.06004157 

nnet 447 : -0.2439305 
nnet mean 447 : -0.3978444 
nnet RMSE 447 : 0.1487735 


s: 448 
logit 448 : -0.466218 
logit mean 448 : -0.4671771 
logit RMSE 448 : 0.08478078 

boosting 448 : -0.4258218 
boosting mean 448 : -0.4626694 
boosting RMSE 448 : 0.1571212 

forest 448 : -0.4797445 
forest mean 448 : -0.4173841 
forest RMSE 448 : 0.06009274 

nnet 448 : -0.4683906 
nnet mean 448 : -0.3980019 
nnet RMSE 448 : 0.1486425 


s: 449 
logit 449 : -0.430537 
logit mean 449 : -0.4670955 
logit RMSE 449 : 0.08469858 

boosting 449 : -0.4840168 
boosting mean 449 : -0.4627169 
boosting RMSE 449 : 0.1569962 

forest 449 : -0.4823468 
forest mean 449 : -0.4175288 
forest RMSE 449 : 0.06015145 

nnet 449 : -0.4773196 
nnet mean 449 : -0.3981785 
nnet RMSE 449 : 0.1485217 


s: 450 
logit 450 : -0.5022353 
logit mean 450 : -0.4671736 
logit RMSE 450 : 0.08474157 

boosting 450 : -0.7540914 
boosting mean 450 : -0.4633644 
boosting RMSE 450 : 0.1577075 

forest 450 : -0.4521537 
forest mean 450 : -0.4176057 
forest RMSE 450 : 0.06013486 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 450 : -0.1538529 
nnet mean 450 : -0.3976356 
nnet RMSE 450 : 0.1488096 


s: 451 
logit 451 : -0.4687173 
logit mean 451 : -0.467177 
logit RMSE 451 : 0.0847094 

boosting 451 : -0.2926937 
boosting mean 451 : -0.462986 
boosting RMSE 451 : 0.1576136 

forest 451 : -0.4152190 
forest mean 451 : -0.4176004 
forest RMSE 451 : 0.06007243 

nnet 451 : -0.1672326 
nnet mean 451 : -0.3971247 
nnet RMSE 451 : 0.1490481 


s: 452 
logit 452 : -0.53883 
logit mean 452 : -0.4673355 
logit RMSE 452 : 0.08486723 

boosting 452 : -0.3441306 
boosting mean 452 : -0.4627231 
boosting RMSE 452 : 0.1574611 

forest 452 : -0.382073 
forest mean 452 : -0.4175218 
forest RMSE 452 : 0.06001186 

nnet 452 : -0.4722961 
nnet mean 452 : -0.397291 
nnet RMSE 452 : 0.148922 


s: 453 
logit 453 : -0.4804703 
logit mean 453 : -0.4673645 
logit RMSE 453 : 0.08485778 

boosting 453 : -0.4928176 
boosting mean 453 : -0.4627895 
boosting RMSE 453 : 0.1573476 

forest 453 : -0.4949997 
forest mean 453 : -0.4176929 
forest RMSE 453 : 0.06011153 

nnet 453 : -0.6119536 
nnet mean 453 : -0.3977649 
nnet RMSE 453 : 0.1490905 


s: 454 
logit 454 : -0.4251139 
logit mean 454 : -0.4672715 
logit RMSE 454 : 0.08477246 

boosting 454 : -0.4370874 
boosting mean 454 : -0.4627329 
boosting RMSE 454 : 0.1571839 

forest 454 : -0.3744321 
forest mean 454 : -0.4175976 
forest RMSE 454 : 0.06005728 

nnet 454 : -0.2818054 
nnet mean 454 : -0.3975095 
nnet RMSE 454 : 0.1490295 


s: 455 
logit 455 : -0.473384 
logit mean 455 : -0.4672849 
logit RMSE 455 : 0.08474911 

boosting 455 : -0.4106897 
boosting mean 455 : -0.4626185 
boosting RMSE 455 : 0.1570119 

forest 455 : -0.4073536 
forest mean 455 : -0.4175751 
forest RMSE 455 : 0.05999224 

nnet 455 : -0.3480771 
nnet mean 455 : -0.3974008 
nnet RMSE 455 : 0.1488855 


s: 456 
logit 456 : -0.5003631 
logit mean 456 : -0.4673574 
logit RMSE 456 : 0.0847865 

boosting 456 : -0.3524499 
boosting mean 456 : -0.4623769 
boosting RMSE 456 : 0.1568554 

forest 456 : -0.3620964 
forest mean 456 : -0.4174534 
forest RMSE 456 : 0.0599527 

nnet 456 : -0.1779294 
nnet mean 456 : -0.3969195 
nnet RMSE 456 : 0.1490853 


s: 457 
logit 457 : -0.4371256 
logit mean 457 : -0.4672913 
logit RMSE 457 : 0.08471149 

boosting 457 : -0.4634078 
boosting mean 457 : -0.4623792 
boosting RMSE 457 : 0.1567118 

forest 457 : -0.3889206 
forest mean 457 : -0.417391 
forest RMSE 457 : 0.05988932 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 457 : -0.3333855 
nnet mean 457 : -0.3967805 
nnet RMSE 457 : 0.1489547 


s: 458 
logit 458 : -0.512181 
logit mean 458 : -0.4673893 
logit RMSE 458 : 0.08478116 

boosting 458 : -0.5158891 
boosting mean 458 : -0.462496 
boosting RMSE 458 : 0.1566342 

forest 458 : -0.5215177 
forest mean 458 : -0.4176183 
forest RMSE 458 : 0.06009277 

nnet 458 : -0.5023434 
nnet mean 458 : -0.397011 
nnet RMSE 458 : 0.1488688 


s: 459 
logit 459 : -0.5468663 
logit mean 459 : -0.4675625 
logit RMSE 459 : 0.08496575 

boosting 459 : -0.3986813 
boosting mean 459 : -0.462357 
boosting RMSE 459 : 0.1564635 

forest 459 : -0.3563016 
forest mean 459 : -0.4174847 
forest RMSE 459 : 0.06006191 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 459 : -0.2427832 
nnet mean 459 : -0.396675 
nnet RMSE 459 : 0.1488875 


s: 460 
logit 460 : -0.497494 
logit mean 460 : -0.4676275 
logit RMSE 460 : 0.08499499 

boosting 460 : -0.6149839 
boosting mean 460 : -0.4626888 
boosting RMSE 460 : 0.1566145 

forest 460 : -0.5116911 
forest mean 460 : -0.4176895 
forest RMSE 460 : 0.06022218 

nnet 460 : -0.3125404 
nnet mean 460 : -0.3964921 
nnet RMSE 460 : 0.1487815 


s: 461 
logit 461 : -0.4225758 
logit mean 461 : -0.4675298 
logit RMSE 461 : 0.08490926 

boosting 461 : -0.488551 
boosting mean 461 : -0.4627449 
boosting RMSE 461 : 0.1564989 

forest 461 : -0.4308716 
forest mean 461 : -0.4177181 
forest RMSE 461 : 0.060174 

nnet 461 : -0.5924925 
nnet mean 461 : -0.3969172 
nnet RMSE 461 : 0.1488902 


s: 462 
logit 462 : -0.3649109 
logit mean 462 : -0.4673077 
logit RMSE 462 : 0.08483303 

boosting 462 : -0.09246387 
boosting mean 462 : -0.4619434 
boosting RMSE 462 : 0.1569828 

forest 462 : -0.2679111 
forest mean 462 : -0.4173939 
forest RMSE 462 : 0.06042217 

nnet 462 : -0.5125824 
nnet mean 462 : -0.3971676 
nnet RMSE 462 : 0.1488212 


s: 463 
logit 463 : -0.4767544 
logit mean 463 : -0.4673281 
logit RMSE 463 : 0.0848164 

boosting 463 : -0.3866289 
boosting mean 463 : -0.4617807 
boosting RMSE 463 : 0.1568144 

forest 463 : -0.5193874 
forest mean 463 : -0.4176142 
forest RMSE 463 : 0.06061137 

nnet 463 : -0.4527759 
nnet mean 463 : -0.3972877 
nnet RMSE 463 : 0.1486806 


s: 464 
logit 464 : -0.4313858 
logit mean 464 : -0.4672506 
logit RMSE 464 : 0.08473749 

boosting 464 : -0.4380282 
boosting mean 464 : -0.4617295 
boosting RMSE 464 : 0.1566553 

forest 464 : -0.3395431 
forest mean 464 : -0.4174459 
forest RMSE 464 : 0.06061104 

nnet 464 : -0.3401058 
nnet mean 464 : -0.3971645 
nnet RMSE 464 : 0.1485463 


s: 465 
logit 465 : -0.4686394 
logit mean 465 : -0.4672536 
logit RMSE 465 : 0.08470615 

boosting 465 : -0.3346124 
boosting mean 465 : -0.4614562 
boosting RMSE 465 : 0.1565161 

forest 465 : -0.3703726 
forest mean 465 : -0.4173447 
forest RMSE 465 : 0.06056141 

nnet 465 : -0.556724 
nnet mean 465 : -0.3975076 
nnet RMSE 465 : 0.1485644 


s: 466 
logit 466 : -0.4547225 
logit mean 466 : -0.4672267 
logit RMSE 466 : 0.08465318 

boosting 466 : -0.5660509 
boosting mean 466 : -0.4616806 
boosting RMSE 466 : 0.1565372 

forest 466 : -0.472348 
forest mean 466 : -0.4174627 
forest RMSE 466 : 0.06058916 

nnet 466 : -0.479055 
nnet mean 466 : -0.3976826 
nnet RMSE 466 : 0.1484501 


s: 467 
logit 467 : -0.496076 
logit mean 467 : -0.4672885 
logit RMSE 467 : 0.08467929 

boosting 467 : -0.361324 
boosting mean 467 : -0.4614657 
boosting RMSE 467 : 0.1563798 

forest 467 : -0.4653697 
forest mean 467 : -0.4175653 
forest RMSE 467 : 0.0605998 

nnet 467 : -0.3762178 
nnet mean 467 : -0.3976366 
nnet RMSE 467 : 0.1482952 


s: 468 
logit 468 : -0.4419787 
logit mean 468 : -0.4672344 
logit RMSE 468 : 0.08461102 

boosting 468 : -0.3499937 
boosting mean 468 : -0.4612275 
boosting RMSE 468 : 0.1562297 

forest 468 : -0.4471693 
forest mean 468 : -0.4176285 
forest RMSE 468 : 0.06057428 

nnet 468 : -0.5730229 
nnet mean 468 : -0.3980114 
nnet RMSE 468 : 0.1483524 


s: 469 
logit 469 : -0.4716611 
logit mean 469 : -0.4672439 
logit RMSE 469 : 0.08458552 

boosting 469 : -0.652762 
boosting mean 469 : -0.4616359 
boosting RMSE 469 : 0.1564989 

forest 469 : -0.4174480 
forest mean 469 : -0.4176282 
forest RMSE 469 : 0.06051503 

nnet 469 : -0.5350117 
nnet mean 469 : -0.3983035 
nnet RMSE 469 : 0.1483252 


s: 470 
logit 470 : -0.5382385 
logit mean 470 : -0.4673949 
logit RMSE 470 : 0.08473575 

boosting 470 : -0.6574104 
boosting mean 470 : -0.4620525 
boosting RMSE 470 : 0.1567825 

forest 470 : -0.3786792 
forest mean 470 : -0.4175453 
forest RMSE 470 : 0.06045862 

nnet 470 : -0.6775719 
nnet mean 470 : -0.3988977 
nnet RMSE 470 : 0.1487195 


s: 471 
logit 471 : -0.4194406 
logit mean 471 : -0.4672931 
logit RMSE 471 : 0.08465049 

boosting 471 : -0.5411613 
boosting mean 471 : -0.4622204 
boosting RMSE 471 : 0.1567510 

forest 471 : -0.4511964 
forest mean 471 : -0.4176167 
forest RMSE 471 : 0.06044046 

nnet 471 : -0.5143555 
nnet mean 471 : -0.3991428 
nnet RMSE 471 : 0.1486550 


s: 472 
logit 472 : -0.4561558 
logit mean 472 : -0.4672695 
logit RMSE 472 : 0.08460026 

boosting 472 : -0.6941425 
boosting mean 472 : -0.4627118 
boosting RMSE 472 : 0.1571691 

forest 472 : -0.4489267 
forest mean 472 : -0.4176831 
forest RMSE 472 : 0.06041838 

nnet 472 : -0.3082547 
nnet mean 472 : -0.3989503 
nnet RMSE 472 : 0.1485574 


s: 473 
logit 473 : -0.4614867 
logit mean 473 : -0.4672573 
logit RMSE 473 : 0.08455806 

boosting 473 : -0.3812924 
boosting mean 473 : -0.4625396 
boosting RMSE 473 : 0.1570053 

forest 473 : -0.4202113 
forest mean 473 : -0.4176884 
forest RMSE 473 : 0.06036163 

nnet 473 : -0.3826721 
nnet mean 473 : -0.3989159 
nnet RMSE 473 : 0.1484024 


s: 474 
logit 474 : -0.4192272 
logit mean 474 : -0.4671559 
logit RMSE 474 : 0.08447343 

boosting 474 : -0.4146535 
boosting mean 474 : -0.4624386 
boosting RMSE 474 : 0.156841 

forest 474 : -0.3040069 
forest mean 474 : -0.4174486 
forest RMSE 474 : 0.06045892 

nnet 474 : -0.3782726 
nnet mean 474 : -0.3988723 
nnet RMSE 474 : 0.1482492 


s: 475 
logit 475 : -0.5329178 
logit mean 475 : -0.4672944 
logit RMSE 475 : 0.08460456 

boosting 475 : -0.4944305 
boosting mean 475 : -0.462506 
boosting RMSE 475 : 0.1567357 

forest 475 : -0.308165 
forest mean 475 : -0.4172185 
forest RMSE 475 : 0.06054205 

nnet 475 : -0.4119667 
nnet mean 475 : -0.3988999 
nnet RMSE 475 : 0.1480941 


s: 476 
logit 476 : -0.4229273 
logit mean 476 : -0.4672012 
logit RMSE 476 : 0.08452218 

boosting 476 : -0.301361 
boosting mean 476 : -0.4621674 
boosting RMSE 476 : 0.1566362 

forest 476 : -0.3494037 
forest mean 476 : -0.417076 
forest RMSE 476 : 0.06052287 

nnet 476 : -0.3682498 
nnet mean 476 : -0.3988355 
nnet RMSE 476 : 0.1479456 


s: 477 
logit 477 : -0.5701542 
logit mean 477 : -0.467417 
logit RMSE 477 : 0.08479221 

boosting 477 : -0.4483875 
boosting mean 477 : -0.4621385 
boosting RMSE 477 : 0.1564877 

forest 477 : -0.3309066 
forest mean 477 : -0.4168954 
forest RMSE 477 : 0.06054211 

nnet 477 : -0.4712656 
nnet mean 477 : -0.3989873 
nnet RMSE 477 : 0.1478264 


s: 478 
logit 478 : -0.4487079 
logit mean 478 : -0.4673779 
logit RMSE 478 : 0.08473276 

boosting 478 : -0.5989214 
boosting mean 478 : -0.4624247 
boosting RMSE 478 : 0.1565884 

forest 478 : -0.4749323 
forest mean 478 : -0.4170168 
forest RMSE 478 : 0.06057578 

nnet 478 : -0.3762023 
nnet mean 478 : -0.3989397 
nnet RMSE 478 : 0.1476757 


s: 479 
logit 479 : -0.4265617 
logit mean 479 : -0.4672927 
logit RMSE 479 : 0.08465297 

boosting 479 : -0.2193954 
boosting mean 479 : -0.4619173 
boosting RMSE 479 : 0.1566424 

forest 479 : -0.4684621 
forest mean 479 : -0.4171242 
forest RMSE 479 : 0.06059332 

nnet 479 : -0.51837 
nnet mean 479 : -0.399189 
nnet RMSE 479 : 0.1476206 


s: 480 
logit 480 : -0.5062452 
logit mean 480 : -0.4673738 
logit RMSE 480 : 0.08470367 

boosting 480 : -0.5350392 
boosting mean 480 : -0.4620697 
boosting RMSE 480 : 0.1566005 

forest 480 : -0.4455434 
forest mean 480 : -0.4171834 
forest RMSE 480 : 0.06056585 

nnet 480 : -0.3594327 
nnet mean 480 : -0.3991062 
nnet RMSE 480 : 0.1474784 


s: 481 
logit 481 : -0.4593351 
logit mean 481 : -0.4673571 
logit RMSE 481 : 0.08465882 

boosting 481 : -0.4056812 
boosting mean 481 : -0.4619524 
boosting RMSE 481 : 0.1564378 

forest 481 : -0.474231 
forest mean 481 : -0.417302 
forest RMSE 481 : 0.06059746 

nnet 481 : -0.5207678 
nnet mean 481 : -0.3993591 
nnet RMSE 481 : 0.1474279 


s: 482 
logit 482 : -0.494098 
logit mean 482 : -0.4674126 
logit RMSE 482 : 0.0846795 

boosting 482 : -0.2500263 
boosting mean 482 : -0.4615128 
boosting RMSE 482 : 0.1564247 

forest 482 : -0.3555727 
forest mean 482 : -0.4171739 
forest RMSE 482 : 0.06056838 

nnet 482 : -0.3062189 
nnet mean 482 : -0.3991659 
nnet RMSE 482 : 0.1473368 


s: 483 
logit 483 : -0.5193877 
logit mean 483 : -0.4675202 
logit RMSE 483 : 0.08476603 

boosting 483 : -0.5565198 
boosting mean 483 : -0.4617095 
boosting RMSE 483 : 0.1564249 

forest 483 : -0.4306512 
forest mean 483 : -0.4172018 
forest RMSE 483 : 0.06052172 

nnet 483 : -0.7844163 
nnet mean 483 : -0.3999635 
nnet RMSE 483 : 0.1482199 


s: 484 
logit 484 : -0.4948602 
logit mean 484 : -0.4675767 
logit RMSE 484 : 0.08478813 

boosting 484 : -0.6187857 
boosting mean 484 : -0.462034 
boosting RMSE 484 : 0.1565794 

forest 484 : -0.5082329 
forest mean 484 : -0.4173899 
forest RMSE 484 : 0.06065899 

nnet 484 : -0.4901202 
nnet mean 484 : -0.4001498 
nnet RMSE 484 : 0.1481234 


s: 485 
logit 485 : -0.4054841 
logit mean 485 : -0.4674487 
logit RMSE 485 : 0.08470104 

boosting 485 : -0.3352477 
boosting mean 485 : -0.4617726 
boosting RMSE 485 : 0.1564455 

forest 485 : -0.2628902 
forest mean 485 : -0.4170714 
forest RMSE 485 : 0.06091541 

nnet 485 : -0.1877143 
nnet mean 485 : -0.3997117 
nnet RMSE 485 : 0.1482842 


s: 486 
logit 486 : -0.463279 
logit mean 486 : -0.4674401 
logit RMSE 486 : 0.08466253 

boosting 486 : -0.4048107 
boosting mean 486 : -0.4616554 
boosting RMSE 486 : 0.1562846 

forest 486 : -0.3892673 
forest mean 486 : -0.4170142 
forest RMSE 486 : 0.06085466 

nnet 486 : -0.438504 
nnet mean 486 : -0.3997916 
nnet RMSE 486 : 0.1481419 


s: 487 
logit 487 : -0.4182521 
logit mean 487 : -0.4673391 
logit RMSE 487 : 0.0845796 

boosting 487 : -0.6323762 
boosting mean 487 : -0.4620059 
boosting RMSE 487 : 0.1564788 

forest 487 : -0.4775104 
forest mean 487 : -0.4171384 
forest RMSE 487 : 0.06089353 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 487 : -0.2567561 
nnet mean 487 : -0.3994979 
nnet RMSE 487 : 0.148132 


s: 488 
logit 488 : -0.4398207 
logit mean 488 : -0.4672827 
logit RMSE 488 : 0.08451213 

boosting 488 : -0.2789966 
boosting mean 488 : -0.4616309 
boosting RMSE 488 : 0.1564143 

forest 488 : -0.3241917 
forest mean 488 : -0.4169479 
forest RMSE 488 : 0.06092782 

nnet 488 : -0.5276343 
nnet mean 488 : -0.3997604 
nnet RMSE 488 : 0.1480929 


s: 489 
logit 489 : -0.5305559 
logit mean 489 : -0.4674121 
logit RMSE 489 : 0.08463185 

boosting 489 : -0.3069923 
boosting mean 489 : -0.4613147 
boosting RMSE 489 : 0.1563109 

forest 489 : -0.300743 
forest mean 489 : -0.4167103 
forest RMSE 489 : 0.06103077 

nnet 489 : -0.4447618 
nnet mean 489 : -0.3998525 
nnet RMSE 489 : 0.1479552 


s: 490 
logit 490 : -0.4720521 
logit mean 490 : -0.4674215 
logit RMSE 490 : 0.08460808 

boosting 490 : -0.4599181 
boosting mean 490 : -0.4613118 
boosting RMSE 490 : 0.1561747 

forest 490 : -0.4684975 
forest mean 490 : -0.416816 
forest RMSE 490 : 0.06104694 

nnet 490 : -0.2315826 
nnet mean 490 : -0.3995091 
nnet RMSE 490 : 0.1479999 


s: 491 
logit 491 : -0.4055465 
logit mean 491 : -0.4672955 
logit RMSE 491 : 0.08452225 

boosting 491 : -0.4835338 
boosting mean 491 : -0.4613571 
boosting RMSE 491 : 0.1560612 

forest 491 : -0.4114884 
forest mean 491 : -0.4168051 
forest RMSE 491 : 0.06098695 

nnet 491 : -0.6122701 
nnet mean 491 : -0.3999424 
nnet RMSE 491 : 0.1481591 


s: 492 
logit 492 : -0.4296930 
logit mean 492 : -0.4672191 
logit RMSE 492 : 0.08444692 

boosting 492 : -0.5474436 
boosting mean 492 : -0.4615321 
boosting RMSE 492 : 0.1560441 

forest 492 : -0.2833316 
forest mean 492 : -0.4165338 
forest RMSE 492 : 0.06115157 

nnet 492 : -0.2046839 
nnet mean 492 : -0.3995455 
nnet RMSE 492 : 0.1482702 


s: 493 
logit 493 : -0.4204292 
logit mean 493 : -0.4671242 
logit RMSE 493 : 0.08436625 

boosting 493 : -0.3318977 
boosting mean 493 : -0.4612691 
boosting RMSE 493 : 0.1559160 

forest 493 : -0.4115954 
forest mean 493 : -0.4165238 
forest RMSE 493 : 0.06109175 

nnet 493 : -0.2300576 
nnet mean 493 : -0.3992017 
nnet RMSE 493 : 0.1483173 


s: 494 
logit 494 : -0.4370372 
logit mean 494 : -0.4670633 
logit RMSE 494 : 0.08429729 

boosting 494 : -0.2002169 
boosting mean 494 : -0.4607407 
boosting RMSE 494 : 0.1560172 

forest 494 : -0.3740839 
forest mean 494 : -0.4164379 
forest RMSE 494 : 0.06104102 

nnet 494 : -0.2313761 
nnet mean 494 : -0.398862 
nnet RMSE 494 : 0.1483613 


s: 495 
logit 495 : -0.4149101 
logit mean 495 : -0.4669579 
logit RMSE 495 : 0.08421476 

boosting 495 : -0.4824072 
boosting mean 495 : -0.4607844 
boosting RMSE 495 : 0.1559036 

forest 495 : -0.3366251 
forest mean 495 : -0.4162767 
forest RMSE 495 : 0.06104582 

nnet 495 : -0.8030888 
nnet mean 495 : -0.3996786 
nnet RMSE 495 : 0.1493146 


s: 496 
logit 496 : -0.5360213 
logit mean 496 : -0.4670972 
logit RMSE 496 : 0.08435123 

boosting 496 : -0.1446002 
boosting mean 496 : -0.460147 
boosting RMSE 496 : 0.1561679 

forest 496 : -0.451121 
forest mean 496 : -0.4163469 
forest RMSE 496 : 0.06102744 

nnet 496 : -0.3977972 
nnet mean 496 : -0.3996748 
nnet RMSE 496 : 0.149164 


s: 497 
logit 497 : -0.438555 
logit mean 497 : -0.4670397 
logit RMSE 497 : 0.08428407 

boosting 497 : -0.3130147 
boosting mean 497 : -0.4598509 
boosting RMSE 497 : 0.1560595 

forest 497 : -0.4024105 
forest mean 497 : -0.4163189 
forest RMSE 497 : 0.06096611 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 497 : -0.1972698 
nnet mean 497 : -0.3992676 
nnet RMSE 497 : 0.1492911 


s: 498 
logit 498 : -0.4189303 
logit mean 498 : -0.4669431 
logit RMSE 498 : 0.08420368 

boosting 498 : -0.519646 
boosting mean 498 : -0.459971 
boosting RMSE 498 : 0.1559949 

forest 498 : -0.4252579 
forest mean 498 : -0.4163368 
forest RMSE 498 : 0.06091538 

nnet 498 : -0.2620297 
nnet mean 498 : -0.398992 
nnet RMSE 498 : 0.1492692 


s: 499 
logit 499 : -0.4686304 
logit mean 499 : -0.4669465 
logit RMSE 499 : 0.08417535 

boosting 499 : -0.5392743 
boosting mean 499 : -0.4601299 
boosting RMSE 499 : 0.1559632 

forest 499 : -0.4211983 
forest mean 499 : -0.4163466 
forest RMSE 499 : 0.06086171 

nnet 499 : -0.3955044 
nnet mean 499 : -0.398985 
nnet RMSE 499 : 0.1491197 


s: 500 
logit 500 : -0.4754428 
logit mean 500 : -0.4669635 
logit RMSE 500 : 0.08415879 

boosting 500 : -0.5503168 
boosting mean 500 : -0.4603103 
boosting RMSE 500 : 0.1559521 

forest 500 : -0.4780145 
forest mean 500 : -0.4164699 
forest RMSE 500 : 0.06090084 

nnet 500 : -0.2857060 
nnet mean 500 : -0.3987584 
nnet RMSE 500 : 0.1490582 


s: 501 
logit 501 : -0.4461131 
logit mean 501 : -0.4669219 
logit RMSE 501 : 0.0841 

boosting 501 : -0.5594977 
boosting mean 501 : -0.4605083 
boosting RMSE 501 : 0.1559593 

forest 501 : -0.3009513 
forest mean 501 : -0.4162393 
forest RMSE 501 : 0.06100075 

nnet 501 : -0.438572 
nnet mean 501 : -0.3988379 
nnet RMSE 501 : 0.1489193 


s: 502 
logit 502 : -0.4998064 
logit mean 502 : -0.4669874 
logit RMSE 502 : 0.0841342 

boosting 502 : -0.5613696 
boosting mean 502 : -0.4607092 
boosting RMSE 502 : 0.1559702 

forest 502 : -0.411588 
forest mean 502 : -0.4162301 
forest RMSE 502 : 0.06094215 

nnet 502 : -0.4813261 
nnet mean 502 : -0.3990022 
nnet RMSE 502 : 0.1488152 


s: 503 
logit 503 : -0.4814719 
logit mean 503 : -0.4670162 
logit RMSE 503 : 0.08412899 

boosting 503 : -0.7274069 
boosting mean 503 : -0.4612394 
boosting RMSE 503 : 0.1564975 

forest 503 : -0.3306488 
forest mean 503 : -0.4160599 
forest RMSE 503 : 0.06096002 

nnet 503 : -0.3607331 
nnet mean 503 : -0.3989261 
nnet RMSE 503 : 0.1486775 


s: 504 
logit 504 : -0.507968 
logit mean 504 : -0.4670974 
logit RMSE 504 : 0.08418297 

boosting 504 : -0.2561312 
boosting mean 504 : -0.4608324 
boosting RMSE 504 : 0.1564735 

forest 504 : -0.3161513 
forest mean 504 : -0.4158617 
forest RMSE 504 : 0.06101394 

nnet 504 : -0.4082589 
nnet mean 504 : -0.3989447 
nnet RMSE 504 : 0.1485304 


s: 505 
logit 505 : -0.5101994 
logit mean 505 : -0.4671828 
logit RMSE 505 : 0.08424243 

boosting 505 : -0.1509887 
boosting mean 505 : -0.4602189 
boosting RMSE 505 : 0.1567107 

forest 505 : -0.5423585 
forest mean 505 : -0.4161122 
forest RMSE 505 : 0.0612818 

nnet 505 : -0.3307873 
nnet mean 505 : -0.3988097 
nnet RMSE 505 : 0.1484152 


s: 506 
logit 506 : -0.520586 
logit mean 506 : -0.4672883 
logit RMSE 506 : 0.0843297 

boosting 506 : -0.2536749 
boosting mean 506 : -0.4598107 
boosting RMSE 506 : 0.1566909 

forest 506 : -0.4125491 
forest mean 506 : -0.4161051 
forest RMSE 506 : 0.06122376 

nnet 506 : -0.2061876 
nnet mean 506 : -0.398429 
nnet RMSE 506 : 0.1485186 


s: 507 
logit 507 : -0.4839654 
logit mean 507 : -0.4673212 
logit RMSE 507 : 0.08432898 

boosting 507 : -0.6819515 
boosting mean 507 : -0.4602489 
boosting RMSE 507 : 0.1570363 

forest 507 : -0.4838594 
forest mean 507 : -0.4162388 
forest RMSE 507 : 0.06127664 

nnet 507 : -0.4717913 
nnet mean 507 : -0.3985737 
nnet RMSE 507 : 0.1484063 


s: 508 
logit 508 : -0.4711784 
logit mean 508 : -0.4673288 
logit RMSE 508 : 0.08430511 

boosting 508 : -0.4289412 
boosting mean 508 : -0.4601872 
boosting RMSE 508 : 0.1568869 

forest 508 : -0.4344372 
forest mean 508 : -0.4162746 
forest RMSE 508 : 0.06123536 

nnet 508 : -0.1902400 
nnet mean 508 : -0.3981636 
nnet RMSE 508 : 0.1485520 


s: 509 
logit 509 : -0.4060490 
logit mean 509 : -0.4672084 
logit RMSE 509 : 0.08422268 

boosting 509 : -0.4800552 
boosting mean 509 : -0.4602263 
boosting RMSE 509 : 0.1567729 

forest 509 : -0.4297092 
forest mean 509 : -0.416301 
forest RMSE 509 : 0.06118935 

nnet 509 : -0.2146599 
nnet mean 509 : -0.3978031 
nnet RMSE 509 : 0.1486332 


s: 510 
logit 510 : -0.5407677 
logit mean 510 : -0.4673527 
logit RMSE 510 : 0.08437064 

boosting 510 : -0.4094255 
boosting mean 510 : -0.4601266 
boosting RMSE 510 : 0.1566197 

forest 510 : -0.4732532 
forest mean 510 : -0.4164127 
forest RMSE 510 : 0.06121533 

nnet 510 : -0.4211641 
nnet mean 510 : -0.3978489 
nnet RMSE 510 : 0.1484903 


s: 511 
logit 511 : -0.4033785 
logit mean 511 : -0.4672275 
logit RMSE 511 : 0.08428818 

boosting 511 : -0.339868 
boosting mean 511 : -0.4598913 
boosting RMSE 511 : 0.1564889 

forest 511 : -0.3381279 
forest mean 511 : -0.4162595 
forest RMSE 511 : 0.06121662 

nnet 511 : -0.299815 
nnet mean 511 : -0.3976571 
nnet RMSE 511 : 0.1484112 


s: 512 
logit 512 : -0.4686518 
logit mean 512 : -0.4672302 
logit RMSE 512 : 0.08426047 

boosting 512 : -0.594573 
boosting mean 512 : -0.4601544 
boosting RMSE 512 : 0.1565724 

forest 512 : -0.5270434 
forest mean 512 : -0.4164758 
forest RMSE 512 : 0.061414 

nnet 512 : -0.3936944 
nnet mean 512 : -0.3976493 
nnet RMSE 512 : 0.1482664 


s: 513 
logit 513 : -0.4716989 
logit mean 513 : -0.467239 
logit RMSE 513 : 0.0842378 

boosting 513 : -0.6151262 
boosting mean 513 : -0.4604564 
boosting RMSE 513 : 0.1567078 

forest 513 : -0.3647488 
forest mean 513 : -0.416375 
forest RMSE 513 : 0.06137385 

nnet 513 : -0.3549518 
nnet mean 513 : -0.3975661 
nnet RMSE 513 : 0.1481352 


s: 514 
logit 514 : -0.4785227 
logit mean 514 : -0.4672609 
logit RMSE 514 : 0.08422706 

boosting 514 : -0.7652594 
boosting mean 514 : -0.4610494 
boosting RMSE 514 : 0.1573821 

forest 514 : -0.4065939 
forest mean 514 : -0.416356 
forest RMSE 514 : 0.06131481 

nnet 514 : -0.5893794 
nnet mean 514 : -0.3979393 
nnet RMSE 514 : 0.1482266 


s: 515 
logit 515 : -0.4360987 
logit mean 515 : -0.4672004 
logit RMSE 515 : 0.08416028 

boosting 515 : -0.7542789 
boosting mean 515 : -0.4616188 
boosting RMSE 515 : 0.1580023 

forest 515 : -0.4353495 
forest mean 515 : -0.4163929 
forest RMSE 515 : 0.06127505 

nnet 515 : -0.4493618 
nnet mean 515 : -0.3980391 
nnet RMSE 515 : 0.1480986 


s: 516 
logit 516 : -0.4919872 
logit mean 516 : -0.4672484 
logit RMSE 516 : 0.08417616 

boosting 516 : -0.5593882 
boosting mean 516 : -0.4618083 
boosting RMSE 516 : 0.1580050 

forest 516 : -0.3623004 
forest mean 516 : -0.416288 
forest RMSE 516 : 0.06123814 

nnet 516 : -0.6817467 
nnet mean 516 : -0.3985889 
nnet RMSE 516 : 0.1484740 


s: 517 
logit 517 : -0.5109896 
logit mean 517 : -0.467333 
logit RMSE 517 : 0.08423626 

boosting 517 : -0.3733424 
boosting mean 517 : -0.4616372 
boosting RMSE 517 : 0.1578565 

forest 517 : -0.4821149 
forest mean 517 : -0.4164154 
forest RMSE 517 : 0.06128539 

nnet 517 : -0.4696539 
nnet mean 517 : -0.3987264 
nnet RMSE 517 : 0.1483620 


s: 518 
logit 518 : -0.4475926 
logit mean 518 : -0.4672949 
logit RMSE 518 : 0.08418089 

boosting 518 : -0.5069839 
boosting mean 518 : -0.4617247 
boosting RMSE 518 : 0.1577741 

forest 518 : -0.4601437 
forest mean 518 : -0.4164998 
forest RMSE 518 : 0.0612832 

nnet 518 : -0.1994254 
nnet mean 518 : -0.3983416 
nnet RMSE 518 : 0.1484804 


s: 519 
logit 519 : -0.4785012 
logit mean 519 : -0.4673165 
logit RMSE 519 : 0.08417031 

boosting 519 : -0.2958058 
boosting mean 519 : -0.461405 
boosting RMSE 519 : 0.1576884 

forest 519 : -0.3666106 
forest mean 519 : -0.4164036 
forest RMSE 519 : 0.06124168 

nnet 519 : -0.4369909 
nnet mean 519 : -0.3984161 
nnet RMSE 519 : 0.1483462 


s: 520 
logit 520 : -0.3989972 
logit mean 520 : -0.4671851 
logit RMSE 520 : 0.08408935 

boosting 520 : -0.5727184 
boosting mean 520 : -0.4616191 
boosting RMSE 520 : 0.1577186 

forest 520 : -0.4260655 
forest mean 520 : -0.4164222 
forest RMSE 520 : 0.06119344 

nnet 520 : -0.3675752 
nnet mean 520 : -0.3983568 
nnet RMSE 520 : 0.1482103 


s: 521 
logit 521 : -0.5203601 
logit mean 521 : -0.4672872 
logit RMSE 521 : 0.08417394 

boosting 521 : -0.3992063 
boosting mean 521 : -0.4614993 
boosting RMSE 521 : 0.1575672 

forest 521 : -0.4909399 
forest mean 521 : -0.4165653 
forest RMSE 521 : 0.06126437 

nnet 521 : -0.4603368 
nnet mean 521 : -0.3984758 
nnet RMSE 521 : 0.1480916 


s: 522 
logit 522 : -0.4928139 
logit mean 522 : -0.4673361 
logit RMSE 522 : 0.08419134 

boosting 522 : -0.5486764 
boosting mean 522 : -0.4616663 
boosting RMSE 522 : 0.1575506 

forest 522 : -0.3416649 
forest mean 522 : -0.4164218 
forest RMSE 522 : 0.06125889 

nnet 522 : -0.5374043 
nnet mean 522 : -0.3987419 
nnet RMSE 522 : 0.1480719 


s: 523 
logit 523 : -0.4714067 
logit mean 523 : -0.4673439 
logit RMSE 523 : 0.08416875 

boosting 523 : -0.4651823 
boosting mean 523 : -0.461673 
boosting RMSE 523 : 0.1574258 

forest 523 : -0.4163289 
forest mean 523 : -0.4164216 
forest RMSE 523 : 0.06120446 

nnet 523 : -0.1373671 
nnet mean 523 : -0.3982421 
nnet RMSE 523 : 0.1483753 


s: 524 
logit 524 : -0.4624704 
logit mean 524 : -0.4673346 
logit RMSE 524 : 0.08413267 

boosting 524 : -0.5758376 
boosting mean 524 : -0.4618909 
boosting RMSE 524 : 0.1574629 

forest 524 : -0.4915237 
forest mean 524 : -0.4165649 
forest RMSE 524 : 0.06127661 

nnet 524 : -0.6421177 
nnet mean 524 : -0.3987076 
nnet RMSE 524 : 0.1486106 


s: 525 
logit 525 : -0.5656581 
logit mean 525 : -0.4675219 
logit RMSE 525 : 0.08436288 

boosting 525 : -0.6367012 
boosting mean 525 : -0.4622239 
boosting RMSE 525 : 0.1576517 

forest 525 : -0.4942754 
forest mean 525 : -0.4167129 
forest RMSE 525 : 0.06135634 

nnet 525 : -0.6246633 
nnet mean 525 : -0.3991380 
nnet RMSE 525 : 0.1487924 


s: 526 
logit 526 : -0.4650762 
logit mean 526 : -0.4675172 
logit RMSE 526 : 0.0843304 

boosting 526 : -0.4201929 
boosting mean 526 : -0.462144 
boosting RMSE 526 : 0.1575043 

forest 526 : -0.4065801 
forest mean 526 : -0.4166937 
forest RMSE 526 : 0.06129866 

nnet 526 : -0.3579467 
nnet mean 526 : -0.3990596 
nnet RMSE 526 : 0.1486622 


s: 527 
logit 527 : -0.4763998 
logit mean 527 : -0.4675341 
logit RMSE 527 : 0.08431605 

boosting 527 : -0.2665984 
boosting mean 527 : -0.4617729 
boosting RMSE 527 : 0.1574620 

forest 527 : -0.4041610 
forest mean 527 : -0.4166699 
forest RMSE 527 : 0.06124074 

nnet 527 : -0.230199 
nnet mean 527 : -0.3987392 
nnet RMSE 527 : 0.1487052 


s: 528 
logit 528 : -0.3914367 
logit mean 528 : -0.46739 
logit RMSE 528 : 0.084237 

boosting 528 : -0.5135447 
boosting mean 528 : -0.461871 
boosting RMSE 528 : 0.1573904 

forest 528 : -0.3479196 
forest mean 528 : -0.4165397 
forest RMSE 528 : 0.06122469 

nnet 528 : -0.3614728 
nnet mean 528 : -0.3986686 
nnet RMSE 528 : 0.1485737 


s: 529 
logit 529 : -0.4965664 
logit mean 529 : -0.4674451 
logit RMSE 529 : 0.084262 

boosting 529 : -0.2476957 
boosting mean 529 : -0.4614661 
boosting RMSE 529 : 0.1573810 

forest 529 : -0.3561367 
forest mean 529 : -0.4164255 
forest RMSE 529 : 0.06119652 

nnet 529 : -0.2759213 
nnet mean 529 : -0.3984366 
nnet RMSE 529 : 0.1485312 


s: 530 
logit 530 : -0.4269558 
logit mean 530 : -0.4673687 
logit RMSE 530 : 0.08419062 

boosting 530 : -0.4309006 
boosting mean 530 : -0.4614084 
boosting RMSE 530 : 0.1572382 

forest 530 : -0.4549079 
forest mean 530 : -0.4164981 
forest RMSE 530 : 0.06118526 

nnet 530 : -0.4550759 
nnet mean 530 : -0.3985435 
nnet RMSE 530 : 0.1484103 


s: 531 
logit 531 : -0.4365027 
logit mean 531 : -0.4673106 
logit RMSE 531 : 0.08412622 

boosting 531 : -0.4848156 
boosting mean 531 : -0.4614525 
boosting RMSE 531 : 0.1571331 

forest 531 : -0.4403144 
forest mean 531 : -0.4165430 
forest RMSE 531 : 0.06115265 

nnet 531 : -0.3341869 
nnet mean 531 : -0.3984223 
nnet RMSE 531 : 0.1482980 


s: 532 
logit 532 : -0.523611 
logit mean 532 : -0.4674164 
logit RMSE 532 : 0.0842178 

boosting 532 : -0.3344473 
boosting mean 532 : -0.4612138 
boosting RMSE 532 : 0.1570111 

forest 532 : -0.3621991 
forest mean 532 : -0.4164408 
forest RMSE 532 : 0.06111713 

nnet 532 : -0.383562 
nnet mean 532 : -0.3983943 
nnet RMSE 532 : 0.1481603 


s: 533 
logit 533 : -0.4114692 
logit mean 533 : -0.4673114 
logit RMSE 533 : 0.08414023 

boosting 533 : -0.4252637 
boosting mean 533 : -0.4611463 
boosting RMSE 533 : 0.1568676 

forest 533 : -0.4252294 
forest mean 533 : -0.4164573 
forest RMSE 533 : 0.06106954 

nnet 533 : -0.4569172 
nnet mean 533 : -0.3985041 
nnet RMSE 533 : 0.1480418 


s: 534 
logit 534 : -0.4034204 
logit mean 534 : -0.4671918 
logit RMSE 534 : 0.08406154 

boosting 534 : -0.4293694 
boosting mean 534 : -0.4610868 
boosting RMSE 534 : 0.1567258 

forest 534 : -0.3639106 
forest mean 534 : -0.4163589 
forest RMSE 534 : 0.06103232 

nnet 534 : -0.1055990 
nnet mean 534 : -0.3979556 
nnet RMSE 534 : 0.1484508 


s: 535 
logit 535 : -0.5196421 
logit mean 535 : -0.4672898 
logit RMSE 535 : 0.08414208 

boosting 535 : -0.6854353 
boosting mean 535 : -0.4615062 
boosting RMSE 535 : 0.1570648 

forest 535 : -0.4418095 
forest mean 535 : -0.4164065 
forest RMSE 535 : 0.06100204 

nnet 535 : -0.3554503 
nnet mean 535 : -0.3978762 
nnet RMSE 535 : 0.1483245 


s: 536 
logit 536 : -0.4527998 
logit mean 536 : -0.4672628 
logit RMSE 536 : 0.08409449 

boosting 536 : -0.3505963 
boosting mean 536 : -0.4612992 
boosting RMSE 536 : 0.1569327 

forest 536 : -0.4185729 
forest mean 536 : -0.4164105 
forest RMSE 536 : 0.06095039 

nnet 536 : -0.4143748 
nnet mean 536 : -0.3979070 
nnet RMSE 536 : 0.1481873 


s: 537 
logit 537 : -0.5092341 
logit mean 537 : -0.467341 
logit RMSE 537 : 0.08414828 

boosting 537 : -0.372986 
boosting mean 537 : -0.4611348 
boosting RMSE 537 : 0.1567908 

forest 537 : -0.3659142 
forest mean 537 : -0.4163165 
forest RMSE 537 : 0.06091137 

nnet 537 : -0.6044812 
nnet mean 537 : -0.3982916 
nnet RMSE 537 : 0.1483120 


s: 538 
logit 538 : -0.487858 
logit mean 538 : -0.4673791 
logit RMSE 538 : 0.08415533 

boosting 538 : -0.2494777 
boosting mean 538 : -0.4607414 
boosting RMSE 538 : 0.1567794 

forest 538 : -0.2865337 
forest mean 538 : -0.4160752 
forest RMSE 538 : 0.06105104 

nnet 538 : -0.4767974 
nnet mean 538 : -0.3984376 
nnet RMSE 538 : 0.1482111 


s: 539 
logit 539 : -0.4560341 
logit mean 539 : -0.4673581 
logit RMSE 539 : 0.08411186 

boosting 539 : -0.4210914 
boosting mean 539 : -0.4606678 
boosting RMSE 539 : 0.1566366 

forest 539 : -0.4137179 
forest mean 539 : -0.4160709 
forest RMSE 539 : 0.06099724 

nnet 539 : -0.6537254 
nnet mean 539 : -0.3989112 
nnet RMSE 539 : 0.1484763 


s: 540 
logit 540 : -0.4862292 
logit mean 540 : -0.467393 
logit RMSE 540 : 0.08411583 

boosting 540 : -0.3154422 
boosting mean 540 : -0.4603989 
boosting RMSE 540 : 0.1565338 

forest 540 : -0.4085012 
forest mean 540 : -0.4160568 
forest RMSE 540 : 0.06094184 

nnet 540 : -0.4832798 
nnet mean 540 : -0.3990674 
nnet RMSE 540 : 0.1483821 


s: 541 
logit 541 : -0.4334847 
logit mean 541 : -0.4673303 
logit RMSE 541 : 0.08405038 

boosting 541 : -0.3930623 
boosting mean 541 : -0.4602744 
boosting RMSE 541 : 0.1563893 

forest 541 : -0.4693518 
forest mean 541 : -0.4161554 
forest RMSE 541 : 0.06095845 

nnet 541 : -0.4587112 
nnet mean 541 : -0.3991777 
nnet RMSE 541 : 0.1482664 


s: 542 
logit 542 : -0.4876078 
logit mean 542 : -0.4673677 
logit RMSE 542 : 0.08405709 

boosting 542 : -0.4282636 
boosting mean 542 : -0.4602154 
boosting RMSE 542 : 0.1562497 

forest 542 : -0.4543236 
forest mean 542 : -0.4162258 
forest RMSE 542 : 0.06094688 

nnet 542 : -0.4138211 
nnet mean 542 : -0.3992047 
nnet RMSE 542 : 0.1481307 


s: 543 
logit 543 : -0.4800142 
logit mean 543 : -0.467391 
logit RMSE 543 : 0.08404982 

boosting 543 : -0.626276 
boosting mean 543 : -0.4605212 
boosting RMSE 543 : 0.1564075 

forest 543 : -0.4487205 
forest mean 543 : -0.4162856 
forest RMSE 543 : 0.06092662 

nnet 543 : -0.390505 
nnet mean 543 : -0.3991887 
nnet RMSE 543 : 0.1479948 


s: 544 
logit 544 : -0.5300986 
logit mean 544 : -0.4675063 
logit RMSE 544 : 0.08415759 

boosting 544 : -0.4983453 
boosting mean 544 : -0.4605907 
boosting RMSE 544 : 0.1563205 

forest 544 : -0.4819734 
forest mean 544 : -0.4164064 
forest RMSE 544 : 0.06097197 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 544 : -0.2241444 
nnet mean 544 : -0.3988669 
nnet RMSE 544 : 0.1480508 


s: 545 
logit 545 : -0.4691091 
logit mean 545 : -0.4675092 
logit RMSE 545 : 0.08413244 

boosting 545 : -0.3985453 
boosting mean 545 : -0.4604769 
boosting RMSE 545 : 0.1561771 

forest 545 : -0.3679719 
forest mean 545 : -0.4163175 
forest RMSE 545 : 0.06093145 

nnet 545 : -0.3245374 
nnet mean 545 : -0.3987305 
nnet RMSE 545 : 0.1479503 


s: 546 
logit 546 : -0.3835859 
logit mean 546 : -0.4673555 
logit RMSE 546 : 0.0840583 

boosting 546 : -0.4139642 
boosting mean 546 : -0.4603917 
boosting RMSE 546 : 0.1560351 

forest 546 : -0.4263448 
forest mean 546 : -0.4163359 
forest RMSE 546 : 0.06088607 

nnet 546 : -0.4095923 
nnet mean 546 : -0.3987504 
nnet RMSE 546 : 0.1478153 


s: 547 
logit 547 : -0.4616018 
logit mean 547 : -0.467345 
logit RMSE 547 : 0.08402272 

boosting 547 : -0.5386242 
boosting mean 547 : -0.4605347 
boosting RMSE 547 : 0.1560051 

forest 547 : -0.4488884 
forest mean 547 : -0.4163954 
forest RMSE 547 : 0.0608663 

nnet 547 : -0.387939 
nnet mean 547 : -0.3987306 
nnet RMSE 547 : 0.147681 


s: 548 
logit 548 : -0.4176468 
logit mean 548 : -0.4672543 
logit RMSE 548 : 0.0839494 

boosting 548 : -0.4671885 
boosting mean 548 : -0.4605468 
boosting RMSE 548 : 0.1558891 

forest 548 : -0.476746 
forest mean 548 : -0.4165055 
forest RMSE 548 : 0.06089904 

nnet 548 : -0.2410513 
nnet mean 548 : -0.3984429 
nnet RMSE 548 : 0.1477023 


s: 549 
logit 549 : -0.432877 
logit mean 549 : -0.4671917 
logit RMSE 549 : 0.08388465 

boosting 549 : -0.4016579 
boosting mean 549 : -0.4604396 
boosting RMSE 549 : 0.1557471 

forest 549 : -0.4060986 
forest mean 549 : -0.4164866 
forest RMSE 549 : 0.06084411 

nnet 549 : -0.4699305 
nnet mean 549 : -0.3985731 
nnet RMSE 549 : 0.1475979 


s: 550 
logit 550 : -0.5183569 
logit mean 550 : -0.4672847 
logit RMSE 550 : 0.08396017 

boosting 550 : -0.1586139 
boosting mean 550 : -0.4598908 
boosting RMSE 550 : 0.1559454 

forest 550 : -0.3308999 
forest mean 550 : -0.4163309 
forest RMSE 550 : 0.06086014 

nnet 550 : -0.3679211 
nnet mean 550 : -0.3985174 
nnet RMSE 550 : 0.1474700 


s: 551 
logit 551 : -0.4835453 
logit mean 551 : -0.4673142 
logit RMSE 551 : 0.08395942 

boosting 551 : -0.6687376 
boosting mean 551 : -0.4602698 
boosting RMSE 551 : 0.1562239 

forest 551 : -0.4378135 
forest mean 551 : -0.4163699 
forest RMSE 551 : 0.06082622 

nnet 551 : -0.07195156 
nnet mean 551 : -0.3979247 
nnet RMSE 551 : 0.1479975 


s: 552 
logit 552 : -0.4400541 
logit mean 552 : -0.4672649 
logit RMSE 552 : 0.08390066 

boosting 552 : -0.3685902 
boosting mean 552 : -0.4601037 
boosting RMSE 552 : 0.1560881 

forest 552 : -0.3858901 
forest mean 552 : -0.4163147 
forest RMSE 552 : 0.06077407 

nnet 552 : -0.4028729 
nnet mean 552 : -0.3979337 
nnet RMSE 552 : 0.1478634 


s: 553 
logit 553 : -0.4620949 
logit mean 553 : -0.4672555 
logit RMSE 553 : 0.08386634 

boosting 553 : -0.4931483 
boosting mean 553 : -0.4601635 
boosting RMSE 553 : 0.1559972 

forest 553 : -0.4506899 
forest mean 553 : -0.4163769 
forest RMSE 553 : 0.06075734 

nnet 553 : -0.5241469 
nnet mean 553 : -0.3981619 
nnet RMSE 553 : 0.1478240 


s: 554 
logit 554 : -0.4181056 
logit mean 554 : -0.4671668 
logit RMSE 554 : 0.08379415 

boosting 554 : -0.4936182 
boosting mean 554 : -0.4602239 
boosting RMSE 554 : 0.1559071 

forest 554 : -0.4429435 
forest mean 554 : -0.4164248 
forest RMSE 554 : 0.0607299 

nnet 554 : -0.05881349 
nnet mean 554 : -0.3975494 
nnet RMSE 554 : 0.1484001 


s: 555 
logit 555 : -0.4098831 
logit mean 555 : -0.4670636 
logit RMSE 555 : 0.08371967 

boosting 555 : -0.63609 
boosting mean 555 : -0.4605408 
boosting RMSE 555 : 0.1560886 

forest 555 : -0.3670963 
forest mean 555 : -0.4163359 
forest RMSE 555 : 0.06069123 

nnet 555 : -0.5356012 
nnet mean 555 : -0.3977981 
nnet RMSE 555 : 0.1483781 


s: 556 
logit 556 : -0.4971135 
logit mean 556 : -0.4671176 
logit RMSE 556 : 0.08374569 

boosting 556 : -0.1937634 
boosting mean 556 : -0.4600609 
boosting RMSE 556 : 0.1561932 

forest 556 : -0.3948181 
forest mean 556 : -0.4162972 
forest RMSE 556 : 0.06063703 

nnet 556 : -0.4897827 
nnet mean 556 : -0.3979636 
nnet RMSE 556 : 0.1482935 


s: 557 
logit 557 : -0.4771646 
logit mean 557 : -0.4671357 
logit RMSE 557 : 0.08373434 

boosting 557 : -0.4878046 
boosting mean 557 : -0.4601108 
boosting RMSE 557 : 0.1560973 

forest 557 : -0.4066243 
forest mean 557 : -0.4162799 
forest RMSE 557 : 0.06058322 

nnet 557 : -0.5351853 
nnet mean 557 : -0.3982099 
nnet RMSE 557 : 0.1482710 


s: 558 
logit 558 : -0.5352607 
logit mean 558 : -0.4672577 
logit RMSE 558 : 0.083855 

boosting 558 : -0.4203398 
boosting mean 558 : -0.4600395 
boosting RMSE 558 : 0.1559598 

forest 558 : -0.4464074 
forest mean 558 : -0.4163339 
forest RMSE 558 : 0.06056078 

nnet 558 : -0.1490797 
nnet mean 558 : -0.3977634 
nnet RMSE 558 : 0.1485184 


s: 559 
logit 559 : -0.4076121 
logit mean 559 : -0.4671510 
logit RMSE 559 : 0.08378058 

boosting 559 : -0.4882942 
boosting mean 559 : -0.46009 
boosting RMSE 559 : 0.1558649 

forest 559 : -0.4370409 
forest mean 559 : -0.4163709 
forest RMSE 559 : 0.06052687 

nnet 559 : 0.06119739 
nnet mean 559 : -0.3969424 
nnet RMSE 559 : 0.1496622 


s: 560 
logit 560 : -0.4658035 
logit mean 560 : -0.4671486 
logit RMSE 560 : 0.08375192 

boosting 560 : -0.4807915 
boosting mean 560 : -0.460127 
boosting RMSE 560 : 0.1557631 

forest 560 : -0.3553449 
forest mean 560 : -0.4162619 
forest RMSE 560 : 0.06050224 

nnet 560 : -0.3197727 
nnet mean 560 : -0.3968046 
nnet RMSE 560 : 0.1495669 


s: 561 
logit 561 : -0.5191179 
logit mean 561 : -0.4672413 
logit RMSE 561 : 0.08382824 

boosting 561 : -0.5499114 
boosting mean 561 : -0.460287 
boosting RMSE 561 : 0.1557529 

forest 561 : -0.4551065 
forest mean 561 : -0.4163312 
forest RMSE 561 : 0.06049305 

nnet 561 : -0.347156 
nnet mean 561 : -0.3967161 
nnet RMSE 561 : 0.1494502 


s: 562 
logit 562 : -0.5093432 
logit mean 562 : -0.4673162 
logit RMSE 562 : 0.08388053 

boosting 562 : -0.3338718 
boosting mean 562 : -0.4600621 
boosting RMSE 562 : 0.1556393 

forest 562 : -0.4692569 
forest mean 562 : -0.4164254 
forest RMSE 562 : 0.06050977 

nnet 562 : -0.3441627 
nnet mean 562 : -0.3966226 
nnet RMSE 562 : 0.1493358 


s: 563 
logit 563 : -0.4758991 
logit mean 563 : -0.4673314 
logit RMSE 563 : 0.08386703 

boosting 563 : -0.4395634 
boosting mean 563 : -0.4600257 
boosting RMSE 563 : 0.1555099 

forest 563 : -0.4317577 
forest mean 563 : -0.4164526 
forest RMSE 563 : 0.06047082 

nnet 563 : -0.3753558 
nnet mean 563 : -0.3965848 
nnet RMSE 563 : 0.1492067 


s: 564 
logit 564 : -0.4244514 
logit mean 564 : -0.4672554 
logit RMSE 564 : 0.08379897 

boosting 564 : -0.3323268 
boosting mean 564 : -0.4597993 
boosting RMSE 564 : 0.1553981 

forest 564 : -0.3359167 
forest mean 564 : -0.4163098 
forest RMSE 564 : 0.06047742 

nnet 564 : -0.4632677 
nnet mean 564 : -0.3967030 
nnet RMSE 564 : 0.1490982 


s: 565 
logit 565 : -0.48572 
logit mean 565 : -0.4672881 
logit RMSE 565 : 0.0838024 

boosting 565 : -0.4940493 
boosting mean 565 : -0.4598599 
boosting RMSE 565 : 0.1553109 

forest 565 : -0.4944587 
forest mean 565 : -0.4164481 
forest RMSE 565 : 0.06055441 

nnet 565 : -0.4210069 
nnet mean 565 : -0.3967461 
nnet RMSE 565 : 0.1489688 


s: 566 
logit 566 : -0.5086579 
logit mean 566 : -0.4673612 
logit RMSE 566 : 0.08385282 

boosting 566 : -0.2594736 
boosting mean 566 : -0.4595058 
boosting RMSE 566 : 0.1552861 

forest 566 : -0.395347 
forest mean 566 : -0.4164108 
forest RMSE 566 : 0.06050121 

nnet 566 : -0.4324748 
nnet mean 566 : -0.3968092 
nnet RMSE 566 : 0.1488434 


s: 567 
logit 567 : -0.4954623 
logit mean 567 : -0.4674107 
logit RMSE 567 : 0.0838747 

boosting 567 : -0.4832878 
boosting mean 567 : -0.4595478 
boosting RMSE 567 : 0.1551885 

forest 567 : -0.482293 
forest mean 567 : -0.416527 
forest RMSE 567 : 0.06054655 

nnet 567 : -0.659856 
nnet mean 567 : -0.3972731 
nnet RMSE 567 : 0.1491119 


s: 568 
logit 568 : -0.4473714 
logit mean 568 : -0.4673755 
logit RMSE 568 : 0.08382441 

boosting 568 : -0.5070691 
boosting mean 568 : -0.4596315 
boosting RMSE 568 : 0.1551169 

forest 568 : -0.3922155 
forest mean 568 : -0.4164842 
forest RMSE 568 : 0.06049411 

nnet 568 : -0.5227376 
nnet mean 568 : -0.397494 
nnet RMSE 568 : 0.1490696 


s: 569 
logit 569 : -0.4732082 
logit mean 569 : -0.4673857 
logit RMSE 569 : 0.08380693 

boosting 569 : -0.5076609 
boosting mean 569 : -0.4597159 
boosting RMSE 569 : 0.1550462 

forest 569 : -0.4098918 
forest mean 569 : -0.4164726 
forest RMSE 569 : 0.06044235 

nnet 569 : -0.8394427 
nnet mean 569 : -0.3982707 
nnet RMSE 569 : 0.1500736 


s: 570 
logit 570 : -0.4758496 
logit mean 570 : -0.4674006 
logit RMSE 570 : 0.08379363 

boosting 570 : -0.5266405 
boosting mean 570 : -0.4598333 
boosting RMSE 570 : 0.1550010 

forest 570 : -0.3780237 
forest mean 570 : -0.4164052 
forest RMSE 570 : 0.06039632 

nnet 570 : -0.4740587 
nnet mean 570 : -0.3984037 
nnet RMSE 570 : 0.1499740 


s: 571 
logit 571 : -0.4239924 
logit mean 571 : -0.4673245 
logit RMSE 571 : 0.08372625 

boosting 571 : -0.4125479 
boosting mean 571 : -0.4597505 
boosting RMSE 571 : 0.1548661 

forest 571 : -0.4058706 
forest mean 571 : -0.4163867 
forest RMSE 571 : 0.06034391 

nnet 571 : -0.4801622 
nnet mean 571 : -0.3985469 
nnet RMSE 571 : 0.1498801 


s: 572 
logit 572 : -0.3754265 
logit mean 572 : -0.4671639 
logit RMSE 572 : 0.08365934 

boosting 572 : -0.2952036 
boosting mean 572 : -0.4594628 
boosting RMSE 572 : 0.1547927 

forest 572 : -0.4174559 
forest mean 572 : -0.4163886 
forest RMSE 572 : 0.06029556 

nnet 572 : -0.4874816 
nnet mean 572 : -0.3987023 
nnet RMSE 572 : 0.1497937 


s: 573 
logit 573 : -0.5422925 
logit mean 573 : -0.467295 
logit RMSE 573 : 0.08379741 

boosting 573 : -0.4753656 
boosting mean 573 : -0.4594906 
boosting RMSE 573 : 0.1546896 

forest 573 : -0.4885285 
forest mean 573 : -0.4165145 
forest RMSE 573 : 0.06035633 

nnet 573 : -0.8018817 
nnet mean 573 : -0.399406 
nnet RMSE 573 : 0.1506017 


s: 574 
logit 574 : -0.4838899 
logit mean 574 : -0.4673239 
logit RMSE 574 : 0.08379757 

boosting 574 : -0.2744508 
boosting mean 574 : -0.4591682 
boosting RMSE 574 : 0.1546436 

forest 574 : -0.4000391 
forest mean 574 : -0.4164858 
forest RMSE 574 : 0.06030374 

nnet 574 : -0.4895453 
nnet mean 574 : -0.399563 
nnet RMSE 574 : 0.1505168 


s: 575 
logit 575 : -0.45803 
logit mean 575 : -0.4673077 
logit RMSE 575 : 0.08375964 

boosting 575 : -0.5413305 
boosting mean 575 : -0.4593111 
boosting RMSE 575 : 0.1546214 

forest 575 : -0.4493426 
forest mean 575 : -0.4165429 
forest RMSE 575 : 0.0602864 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 575 : -0.2416830 
nnet mean 575 : -0.3992884 
nnet RMSE 575 : 0.1505308 


s: 576 
logit 576 : -0.4928551 
logit mean 576 : -0.4673521 
logit RMSE 576 : 0.08377629 

boosting 576 : -0.5114961 
boosting mean 576 : -0.4594017 
boosting RMSE 576 : 0.1545570 

forest 576 : -0.4585042 
forest mean 576 : -0.4166158 
forest RMSE 576 : 0.06028335 

nnet 576 : -0.2985004 
nnet mean 576 : -0.3991135 
nnet RMSE 576 : 0.1504595 


s: 577 
logit 577 : -0.4890592 
logit mean 577 : -0.4673897 
logit RMSE 577 : 0.08378573 

boosting 577 : -0.397933 
boosting mean 577 : -0.4592951 
boosting RMSE 577 : 0.154423 

forest 577 : -0.4996276 
forest mean 577 : -0.4167597 
forest RMSE 577 : 0.06037373 

nnet 577 : -0.4785579 
nnet mean 577 : -0.3992511 
nnet RMSE 577 : 0.1503646 


s: 578 
logit 578 : -0.4897742 
logit mean 578 : -0.4674284 
logit RMSE 578 : 0.08379646 

boosting 578 : -0.6742555 
boosting mean 578 : -0.459667 
boosting RMSE 578 : 0.1547105 

forest 578 : -0.4060576 
forest mean 578 : -0.4167411 
forest RMSE 578 : 0.060322 

nnet 578 : -0.3000154 
nnet mean 578 : -0.3990795 
nnet RMSE 578 : 0.1502920 


s: 579 
logit 579 : -0.4386097 
logit mean 579 : -0.4673787 
logit RMSE 579 : 0.08373944 

boosting 579 : -0.6677673 
boosting mean 579 : -0.4600265 
boosting RMSE 579 : 0.1549769 

forest 579 : -0.36196 
forest mean 579 : -0.4166465 
forest RMSE 579 : 0.06029062 

nnet 579 : -0.3254456 
nnet mean 579 : -0.3989523 
nnet RMSE 579 : 0.1501942 


s: 580 
logit 580 : -0.4467345 
logit mean 580 : -0.4673431 
logit RMSE 580 : 0.08368972 

boosting 580 : -0.4142499 
boosting mean 580 : -0.4599475 
boosting RMSE 580 : 0.1548444 

forest 580 : -0.4480178 
forest mean 580 : -0.4167006 
forest RMSE 580 : 0.06027161 

nnet 580 : -0.3156154 
nnet mean 580 : -0.3988086 
nnet RMSE 580 : 0.1501055 


s: 581 
logit 581 : -0.4615033 
logit mean 581 : -0.467333 
logit RMSE 581 : 0.08365659 

boosting 581 : -0.4490126 
boosting mean 581 : -0.4599287 
boosting RMSE 581 : 0.1547244 

forest 581 : -0.3809302 
forest mean 581 : -0.4166390 
forest RMSE 581 : 0.06022492 

nnet 581 : -0.5990211 
nnet mean 581 : -0.3991532 
nnet RMSE 581 : 0.1502034 


s: 582 
logit 582 : -0.3496200 
logit mean 582 : -0.4671308 
logit RMSE 582 : 0.08361077 

boosting 582 : -0.4439174 
boosting mean 582 : -0.4599012 
boosting RMSE 582 : 0.1546021 

forest 582 : -0.388614 
forest mean 582 : -0.4165909 
forest RMSE 582 : 0.060175 

nnet 582 : -0.2895612 
nnet mean 582 : -0.3989649 
nnet RMSE 582 : 0.1501441 


s: 583 
logit 583 : -0.5226123 
logit mean 583 : -0.4672259 
logit RMSE 583 : 0.08369323 

boosting 583 : -0.4269655 
boosting mean 583 : -0.4598447 
boosting RMSE 583 : 0.1544735 

forest 583 : -0.3970636 
forest mean 583 : -0.4165574 
forest RMSE 583 : 0.0601235 

nnet 583 : -0.3331632 
nnet mean 583 : -0.398852 
nnet RMSE 583 : 0.1500408 


s: 584 
logit 584 : -0.4787147 
logit mean 584 : -0.4672456 
logit RMSE 584 : 0.08368496 

boosting 584 : -0.1070223 
boosting mean 584 : -0.4592406 
boosting RMSE 584 : 0.1548166 

forest 584 : -0.4201972 
forest mean 584 : -0.4165636 
forest RMSE 584 : 0.06007781 

nnet 584 : -0.3632954 
nnet mean 584 : -0.3987911 
nnet RMSE 584 : 0.14992 


s: 585 
logit 585 : -0.4553884 
logit mean 585 : -0.4672253 
logit RMSE 585 : 0.08364476 

boosting 585 : -0.4184271 
boosting mean 585 : -0.4591708 
boosting RMSE 585 : 0.1546861 

forest 585 : -0.3728651 
forest mean 585 : -0.4164889 
forest RMSE 585 : 0.06003693 

nnet 585 : -0.3919861 
nnet mean 585 : -0.3987795 
nnet RMSE 585 : 0.1497922 


s: 586 
logit 586 : -0.4569686 
logit mean 586 : -0.4672078 
logit RMSE 586 : 0.08360649 

boosting 586 : -0.4772204 
boosting mean 586 : -0.4592016 
boosting RMSE 586 : 0.154587 

forest 586 : -0.4065103 
forest mean 586 : -0.4164719 
forest RMSE 586 : 0.05998628 

nnet 586 : -0.5105793 
nnet mean 586 : -0.3989703 
nnet RMSE 586 : 0.149734 


s: 587 
logit 587 : -0.5060613 
logit mean 587 : -0.467274 
logit RMSE 587 : 0.08364987 

boosting 587 : -0.537019 
boosting mean 587 : -0.4593342 
boosting RMSE 587 : 0.1545588 

forest 587 : -0.3365696 
forest mean 587 : -0.4163358 
forest RMSE 587 : 0.05999232 

nnet 587 : -0.4912171 
nnet mean 587 : -0.3991274 
nnet RMSE 587 : 0.1496538 


s: 588 
logit 588 : -0.429713 
logit mean 588 : -0.4672101 
logit RMSE 588 : 0.08358769 

boosting 588 : -0.3637695 
boosting mean 588 : -0.4591716 
boosting RMSE 588 : 0.1544345 

forest 588 : -0.380056 
forest mean 588 : -0.4162741 
forest RMSE 588 : 0.05994692 

nnet 588 : -0.4563925 
nnet mean 588 : -0.3992248 
nnet RMSE 588 : 0.1495445 


s: 589 
logit 589 : -0.5166142 
logit mean 589 : -0.467294 
logit RMSE 589 : 0.08365481 

boosting 589 : -0.2384895 
boosting mean 589 : -0.458797 
boosting RMSE 589 : 0.1544468 

forest 589 : -0.4681602 
forest mean 589 : -0.4163622 
forest RMSE 589 : 0.05996182 

nnet 589 : -0.4771508 
nnet mean 589 : -0.3993571 
nnet RMSE 589 : 0.1494514 


s: 590 
logit 590 : -0.5130621 
logit mean 590 : -0.4673716 
logit RMSE 590 : 0.0837134 

boosting 590 : -0.2743199 
boosting mean 590 : -0.4584843 
boosting RMSE 590 : 0.1544026 

forest 590 : -0.4773538 
forest mean 590 : -0.4164656 
forest RMSE 590 : 0.05999556 

nnet 590 : -0.6237959 
nnet mean 590 : -0.3997375 
nnet RMSE 590 : 0.1496086 


s: 591 
logit 591 : -0.4405334 
logit mean 591 : -0.4673262 
logit RMSE 591 : 0.08365915 

boosting 591 : -0.5098669 
boosting mean 591 : -0.4585712 
boosting RMSE 591 : 0.1543381 

forest 591 : -0.4486511 
forest mean 591 : -0.41652 
forest RMSE 591 : 0.05997818 

nnet 591 : -0.5453722 
nnet mean 591 : -0.3999840 
nnet RMSE 591 : 0.1496016 


s: 592 
logit 592 : -0.5511481 
logit mean 592 : -0.4674678 
logit RMSE 592 : 0.08381899 

boosting 592 : -0.4834524 
boosting mean 592 : -0.4586133 
boosting RMSE 592 : 0.1542458 

forest 592 : -0.4350720 
forest mean 592 : -0.4165513 
forest RMSE 592 : 0.05994484 

nnet 592 : -0.3867388 
nnet mean 592 : -0.3999616 
nnet RMSE 592 : 0.1494761 


s: 593 
logit 593 : -0.4343718 
logit mean 593 : -0.467412 
logit RMSE 593 : 0.08376018 

boosting 593 : -0.4774749 
boosting mean 593 : -0.4586451 
boosting RMSE 593 : 0.1541485 

forest 593 : -0.4316399 
forest mean 593 : -0.4165768 
forest RMSE 593 : 0.05990836 

nnet 593 : -0.3901895 
nnet mean 593 : -0.3999451 
nnet RMSE 593 : 0.1493506 


s: 594 
logit 594 : -0.4269492 
logit mean 594 : -0.4673438 
logit RMSE 594 : 0.08369695 

boosting 594 : -0.6357922 
boosting mean 594 : -0.4589433 
boosting RMSE 594 : 0.1543223 

forest 594 : -0.4092380 
forest mean 594 : -0.4165644 
forest RMSE 594 : 0.05985911 

nnet 594 : -0.2048923 
nnet mean 594 : -0.3996167 
nnet RMSE 594 : 0.1494394 


s: 595 
logit 595 : -0.4975054 
logit mean 595 : -0.4673945 
logit RMSE 595 : 0.08372206 

boosting 595 : -0.4752011 
boosting mean 595 : -0.4589706 
boosting RMSE 595 : 0.1542234 

forest 595 : -0.4428829 
forest mean 595 : -0.4166087 
forest RMSE 595 : 0.05983462 

nnet 595 : -0.2984733 
nnet mean 595 : -0.3994467 
nnet RMSE 595 : 0.1493718 


s: 596 
logit 596 : -0.5177373 
logit mean 596 : -0.467479 
logit RMSE 596 : 0.0837907 

boosting 596 : -0.5235131 
boosting mean 596 : -0.4590789 
boosting RMSE 596 : 0.1541770 

forest 596 : -0.4295826 
forest mean 596 : -0.4166304 
forest RMSE 596 : 0.05979668 

nnet 596 : -0.5585507 
nnet mean 596 : -0.3997137 
nnet RMSE 596 : 0.1493876 


s: 597 
logit 597 : -0.5521057 
logit mean 597 : -0.4676208 
logit RMSE 597 : 0.08395163 

boosting 597 : -0.4406203 
boosting mean 597 : -0.459048 
boosting RMSE 597 : 0.1540568 

forest 597 : -0.4284063 
forest mean 597 : -0.4166502 
forest RMSE 597 : 0.05975789 

nnet 597 : -0.4570232 
nnet mean 597 : -0.3998097 
nnet RMSE 597 : 0.1492807 


s: 598 
logit 598 : -0.4811137 
logit mean 598 : -0.4676433 
logit RMSE 598 : 0.08394696 

boosting 598 : -0.4851952 
boosting mean 598 : -0.4590917 
boosting RMSE 598 : 0.1539673 

forest 598 : -0.404641 
forest mean 598 : -0.4166301 
forest RMSE 598 : 0.05970821 

nnet 598 : -0.3852343 
nnet mean 598 : -0.3997853 
nnet RMSE 598 : 0.1491571 


s: 599 
logit 599 : -0.4849928 
logit mean 599 : -0.4676723 
logit RMSE 599 : 0.08394872 

boosting 599 : -0.1941516 
boosting mean 599 : -0.4586494 
boosting RMSE 599 : 0.1540685 

forest 599 : -0.3918489 
forest mean 599 : -0.4165887 
forest RMSE 599 : 0.05965928 

nnet 599 : -0.4601497 
nnet mean 599 : -0.3998861 
nnet RMSE 599 : 0.1490528 


s: 600 
logit 600 : -0.4646488 
logit mean 600 : -0.4676672 
logit RMSE 600 : 0.08392024 

boosting 600 : -0.4606452 
boosting mean 600 : -0.4586527 
boosting RMSE 600 : 0.1539599 

forest 600 : -0.3568950 
forest mean 600 : -0.4164892 
forest RMSE 600 : 0.05963551 

nnet 600 : -0.1573499 
nnet mean 600 : -0.3994819 
nnet RMSE 600 : 0.1492576 


s: 601 
logit 601 : -0.5677753 
logit mean 601 : -0.4678338 
logit RMSE 601 : 0.08412922 

boosting 601 : -0.09379367 
boosting mean 601 : -0.4580457 
boosting RMSE 601 : 0.1543381 

forest 601 : -0.405643 
forest mean 601 : -0.4164712 
forest RMSE 601 : 0.05958632 

nnet 601 : -0.2162088 
nnet mean 601 : -0.3991769 
nnet RMSE 601 : 0.1493217 


s: 602 
logit 602 : -0.4875515 
logit mean 602 : -0.4678666 
logit RMSE 602 : 0.08413502 

boosting 602 : -0.3150311 
boosting mean 602 : -0.4578081 
boosting RMSE 602 : 0.1542487 

forest 602 : -0.3212238 
forest mean 602 : -0.4163130 
forest RMSE 602 : 0.05962332 

nnet 602 : -0.2829094 
nnet mean 602 : -0.3989838 
nnet RMSE 602 : 0.1492739 


s: 603 
logit 603 : -0.5379028 
logit mean 603 : -0.4679827 
logit RMSE 603 : 0.0842526 

boosting 603 : -0.3360329 
boosting mean 603 : -0.4576061 
boosting RMSE 603 : 0.1541428 

forest 603 : -0.3633967 
forest mean 603 : -0.4162252 
forest RMSE 603 : 0.0595925 

nnet 603 : -0.3114232 
nnet mean 603 : -0.3988386 
nnet RMSE 603 : 0.1491937 


s: 604 
logit 604 : -0.455514 
logit mean 604 : -0.4679621 
logit RMSE 604 : 0.08421312 

boosting 604 : -0.6674428 
boosting mean 604 : -0.4579536 
boosting RMSE 604 : 0.1543991 

forest 604 : -0.4089306 
forest mean 604 : -0.4162131 
forest RMSE 604 : 0.05954426 

nnet 604 : -0.3790511 
nnet mean 604 : -0.3988058 
nnet RMSE 604 : 0.1490726 


s: 605 
logit 605 : -0.4265687 
logit mean 605 : -0.4678937 
logit RMSE 605 : 0.08415043 

boosting 605 : -0.4940843 
boosting mean 605 : -0.4580133 
boosting RMSE 605 : 0.1543188 

forest 605 : -0.4657222 
forest mean 605 : -0.416295 
forest RMSE 605 : 0.059555 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 605 : -0.2025045 
nnet mean 605 : -0.3984814 
nnet RMSE 605 : 0.1491656 


s: 606 
logit 606 : -0.4373908 
logit mean 606 : -0.4678433 
logit RMSE 606 : 0.08409469 

boosting 606 : -0.3921472 
boosting mean 606 : -0.4579046 
boosting RMSE 606 : 0.1541918 

forest 606 : -0.4446635 
forest mean 606 : -0.4163418 
forest RMSE 606 : 0.0595335 

nnet 606 : -0.4725369 
nnet mean 606 : -0.3986036 
nnet RMSE 606 : 0.1490716 


s: 607 
logit 607 : -0.4711907 
logit mean 607 : -0.4678488 
logit RMSE 607 : 0.08407506 

boosting 607 : -0.5148989 
boosting mean 607 : -0.4579985 
boosting RMSE 607 : 0.1541353 

forest 607 : -0.4743893 
forest mean 607 : -0.4164374 
forest RMSE 607 : 0.05956102 

nnet 607 : -0.5063411 
nnet mean 607 : -0.3987810 
nnet RMSE 607 : 0.1490113 


s: 608 
logit 608 : -0.3765111 
logit mean 608 : -0.4676986 
logit RMSE 608 : 0.08401129 

boosting 608 : -0.7813039 
boosting mean 608 : -0.4585302 
boosting RMSE 608 : 0.1547829 

forest 608 : -0.4511452 
forest mean 608 : -0.4164945 
forest RMSE 608 : 0.05954815 

nnet 608 : -0.4661861 
nnet mean 608 : -0.3988919 
nnet RMSE 608 : 0.1489129 


s: 609 
logit 609 : -0.4146322 
logit mean 609 : -0.4676115 
logit RMSE 609 : 0.08394438 

boosting 609 : -0.4354435 
boosting mean 609 : -0.4584923 
boosting RMSE 609 : 0.1546624 

forest 609 : -0.3958189 
forest mean 609 : -0.4164605 
forest RMSE 609 : 0.05949948 

nnet 609 : -0.4065331 
nnet mean 609 : -0.3989045 
nnet RMSE 609 : 0.1487908 


s: 610 
logit 610 : -0.4680336 
logit mean 610 : -0.4676122 
logit RMSE 610 : 0.08392076 

boosting 610 : -0.4448011 
boosting mean 610 : -0.4584699 
boosting RMSE 610 : 0.1545462 

forest 610 : -0.4361001 
forest mean 610 : -0.4164927 
forest RMSE 610 : 0.05946866 

nnet 610 : -0.2555076 
nnet mean 610 : -0.3986694 
nnet RMSE 610 : 0.1487839 


s: 611 
logit 611 : -0.5416242 
logit mean 611 : -0.4677333 
logit RMSE 611 : 0.08404758 

boosting 611 : -0.3776952 
boosting mean 611 : -0.4583377 
boosting RMSE 611 : 0.1544224 

forest 611 : -0.5206978 
forest mean 611 : -0.4166633 
forest RMSE 611 : 0.05962027 

nnet 611 : -0.4283407 
nnet mean 611 : -0.3987179 
nnet RMSE 611 : 0.1486665 


s: 612 
logit 612 : -0.4280527 
logit mean 612 : -0.4676685 
logit RMSE 612 : 0.08398654 

boosting 612 : -0.6005428 
boosting mean 612 : -0.45857 
boosting RMSE 612 : 0.1545089 

forest 612 : -0.3764426 
forest mean 612 : -0.4165976 
forest RMSE 612 : 0.05957915 

nnet 612 : -0.4061 
nnet mean 612 : -0.39873 
nnet RMSE 612 : 0.1485452 


s: 613 
logit 613 : -0.4760462 
logit mean 613 : -0.4676821 
logit RMSE 613 : 0.0839742 

boosting 613 : -0.2947484 
boosting mean 613 : -0.4583028 
boosting RMSE 613 : 0.1544414 

forest 613 : -0.4282179 
forest mean 613 : -0.4166165 
forest RMSE 613 : 0.05954144 

nnet 613 : -0.4263273 
nnet mean 613 : -0.398775 
nnet RMSE 613 : 0.1484278 


s: 614 
logit 614 : -0.4547238 
logit mean 614 : -0.467661 
logit RMSE 614 : 0.08393485 

boosting 614 : -0.3046335 
boosting mean 614 : -0.4580525 
boosting RMSE 614 : 0.1543636 

forest 614 : -0.4234656 
forest mean 614 : -0.4166277 
forest RMSE 614 : 0.05950047 

nnet 614 : -0.5529746 
nnet mean 614 : -0.3990262 
nnet RMSE 614 : 0.1484353 


s: 615 
logit 615 : -0.466146 
logit mean 615 : -0.4676586 
logit RMSE 615 : 0.08390898 

boosting 615 : -0.3536116 
boosting mean 615 : -0.4578827 
boosting RMSE 615 : 0.1542493 

forest 615 : -0.370268 
forest mean 615 : -0.4165523 
forest RMSE 615 : 0.05946416 

nnet 615 : -0.3019919 
nnet mean 615 : -0.3988684 
nnet RMSE 615 : 0.1483672 


s: 616 
logit 616 : -0.3819941 
logit mean 616 : -0.4675195 
logit RMSE 616 : 0.08384398 

boosting 616 : -0.2885205 
boosting mean 616 : -0.4576078 
boosting RMSE 616 : 0.1541895 

forest 616 : -0.3610049 
forest mean 616 : -0.4164621 
forest RMSE 616 : 0.05943665 

nnet 616 : -0.3342144 
nnet mean 616 : -0.3987634 
nnet RMSE 616 : 0.1482704 


s: 617 
logit 617 : -0.4761591 
logit mean 617 : -0.4675335 
logit RMSE 617 : 0.0838321 

boosting 617 : -0.4791174 
boosting mean 617 : -0.4576426 
boosting RMSE 617 : 0.1540975 

forest 617 : -0.3934289 
forest mean 617 : -0.4164248 
forest RMSE 617 : 0.05938905 

nnet 617 : -0.6183016 
nnet mean 617 : -0.3991192 
nnet RMSE 617 : 0.1484107 


s: 618 
logit 618 : -0.4672277 
logit mean 618 : -0.467533 
logit RMSE 618 : 0.08380789 

boosting 618 : -0.4166432 
boosting mean 618 : -0.4575763 
boosting RMSE 618 : 0.1539742 

forest 618 : -0.3537405 
forest mean 618 : -0.4163234 
forest RMSE 618 : 0.05937015 

nnet 618 : -0.2757710 
nnet mean 618 : -0.3989196 
nnet RMSE 618 : 0.1483747 


s: 619 
logit 619 : -0.5693304 
logit mean 619 : -0.4676975 
logit RMSE 619 : 0.08401629 

boosting 619 : -0.6272618 
boosting mean 619 : -0.4578504 
boosting RMSE 619 : 0.1541207 

forest 619 : -0.3758032 
forest mean 619 : -0.4162579 
forest RMSE 619 : 0.05933015 

nnet 619 : -0.4769205 
nnet mean 619 : -0.3990457 
nnet RMSE 619 : 0.1482871 


s: 620 
logit 620 : -0.4730588 
logit mean 620 : -0.4677061 
logit RMSE 620 : 0.08399976 

boosting 620 : -0.3509201 
boosting mean 620 : -0.4576779 
boosting RMSE 620 : 0.1540090 

forest 620 : -0.4887447 
forest mean 620 : -0.4163748 
forest RMSE 620 : 0.05938932 

nnet 620 : -0.3455507 
nnet mean 620 : -0.3989594 
nnet RMSE 620 : 0.1481836 


s: 621 
logit 621 : -0.5087229 
logit mean 621 : -0.4677722 
logit RMSE 621 : 0.08404542 

boosting 621 : -0.5014398 
boosting mean 621 : -0.4577484 
boosting RMSE 621 : 0.1539387 

forest 621 : -0.4417835 
forest mean 621 : -0.4164157 
forest RMSE 621 : 0.05936517 

nnet 621 : -0.3799234 
nnet mean 621 : -0.3989287 
nnet RMSE 621 : 0.1480664 


s: 622 
logit 622 : -0.4360953 
logit mean 622 : -0.4677212 
logit RMSE 622 : 0.0839903 

boosting 622 : -0.2461234 
boosting mean 622 : -0.4574082 
boosting RMSE 622 : 0.1539386 

forest 622 : -0.4347321 
forest mean 622 : -0.4164452 
forest RMSE 622 : 0.05933377 

nnet 622 : -0.1942582 
nnet mean 622 : -0.3985997 
nnet RMSE 622 : 0.1481771 


s: 623 
logit 623 : -0.3812808 
logit mean 623 : -0.4675825 
logit RMSE 623 : 0.08392622 

boosting 623 : -0.4377698 
boosting mean 623 : -0.4573766 
boosting RMSE 623 : 0.1538225 

forest 623 : -0.4483686 
forest mean 623 : -0.4164964 
forest RMSE 623 : 0.0593178 

nnet 623 : -0.55664 
nnet mean 623 : -0.3988533 
nnet RMSE 623 : 0.1481911 


s: 624 
logit 624 : -0.4047105 
logit mean 624 : -0.4674817 
logit RMSE 624 : 0.08385916 

boosting 624 : -0.3761297 
boosting mean 624 : -0.4572464 
boosting RMSE 624 : 0.1537022 

forest 624 : -0.4366087 
forest mean 624 : -0.4165286 
forest RMSE 624 : 0.05928836 

nnet 624 : -0.5875457 
nnet mean 624 : -0.3991557 
nnet RMSE 624 : 0.1482625 


s: 625 
logit 625 : -0.4716186 
logit mean 625 : -0.4674883 
logit RMSE 625 : 0.083841 

boosting 625 : -0.4133493 
boosting mean 625 : -0.4571762 
boosting RMSE 625 : 0.1535801 

forest 625 : -0.4255929 
forest mean 625 : -0.4165431 
forest RMSE 625 : 0.05924976 

nnet 625 : -0.3973997 
nnet mean 625 : -0.3991529 
nnet RMSE 625 : 0.1481439 


s: 626 
logit 626 : -0.5088906 
logit mean 626 : -0.4675545 
logit RMSE 626 : 0.08388698 

boosting 626 : -0.4926812 
boosting mean 626 : -0.4572329 
boosting RMSE 626 : 0.1535021 

forest 626 : -0.4325171 
forest mean 626 : -0.4165687 
forest RMSE 626 : 0.05921668 

nnet 626 : -0.3250221 
nnet mean 626 : -0.3990345 
nnet RMSE 626 : 0.1480559 


s: 627 
logit 627 : -0.5656576 
logit mean 627 : -0.4677109 
logit RMSE 627 : 0.08408074 

boosting 627 : -0.2280702 
boosting mean 627 : -0.4568674 
boosting RMSE 627 : 0.1535332 

forest 627 : -0.2976414 
forest mean 627 : -0.416379 
forest RMSE 627 : 0.05931047 

nnet 627 : -0.2659662 
nnet mean 627 : -0.3988223 
nnet RMSE 627 : 0.1480346 


s: 628 
logit 628 : -0.4734784 
logit mean 628 : -0.4677201 
logit RMSE 628 : 0.08406492 

boosting 628 : -0.4657172 
boosting mean 628 : -0.4568815 
boosting RMSE 628 : 0.1534333 

forest 628 : -0.3485035 
forest mean 628 : -0.4162709 
forest RMSE 628 : 0.05929885 

nnet 628 : -0.4675143 
nnet mean 628 : -0.3989317 
nnet RMSE 628 : 0.1479412 


s: 629 
logit 629 : -0.4707353 
logit mean 629 : -0.4677249 
logit RMSE 629 : 0.0840454 

boosting 629 : -0.3703474 
boosting mean 629 : -0.4567440 
boosting RMSE 629 : 0.1533159 

forest 629 : -0.3417479 
forest mean 629 : -0.4161524 
forest RMSE 629 : 0.0592972 

nnet 629 : -0.2385080 
nnet mean 629 : -0.3986766 
nnet RMSE 629 : 0.1479637 


s: 630 
logit 630 : -0.4188804 
logit mean 630 : -0.4676474 
logit RMSE 630 : 0.08398204 

boosting 630 : -0.4468758 
boosting mean 630 : -0.4567283 
boosting RMSE 630 : 0.1532055 

forest 630 : -0.4005795 
forest mean 630 : -0.4161277 
forest RMSE 630 : 0.05925012 

nnet 630 : -0.2247087 
nnet mean 630 : -0.3984005 
nnet RMSE 630 : 0.1480111 


s: 631 
logit 631 : -0.454817 
logit mean 631 : -0.4676271 
logit RMSE 631 : 0.08394384 

boosting 631 : -0.4027938 
boosting mean 631 : -0.4566428 
boosting RMSE 631 : 0.1530841 

forest 631 : -0.3639882 
forest mean 631 : -0.4160451 
forest RMSE 631 : 0.05922051 

nnet 631 : -0.3713262 
nnet mean 631 : -0.3983576 
nnet RMSE 631 : 0.1478982 


s: 632 
logit 632 : -0.5332921 
logit mean 632 : -0.4677310 
logit RMSE 632 : 0.08404481 

boosting 632 : -0.541957 
boosting mean 632 : -0.4567778 
boosting RMSE 632 : 0.1530672 

forest 632 : -0.4249772 
forest mean 632 : -0.4160592 
forest RMSE 632 : 0.05918198 

nnet 632 : -0.6054484 
nnet mean 632 : -0.3986852 
nnet RMSE 632 : 0.1480069 


s: 633 
logit 633 : -0.472497 
logit mean 633 : -0.4677385 
logit RMSE 633 : 0.08402782 

boosting 633 : -0.7961449 
boosting mean 633 : -0.4573139 
boosting RMSE 633 : 0.1537545 

forest 633 : -0.4363249 
forest mean 633 : -0.4160912 
forest RMSE 633 : 0.05915284 

nnet 633 : -0.5115217 
nnet mean 633 : -0.3988635 
nnet RMSE 633 : 0.1479564 


s: 634 
logit 634 : -0.4795505 
logit mean 634 : -0.4677571 
logit RMSE 634 : 0.08402095 

boosting 634 : -0.6389406 
boosting mean 634 : -0.4576004 
boosting RMSE 634 : 0.1539260 

forest 634 : -0.4083262 
forest mean 634 : -0.416079 
forest RMSE 634 : 0.0591071 

nnet 634 : -0.4407129 
nnet mean 634 : -0.3989295 
nnet RMSE 634 : 0.1478485 


s: 635 
logit 635 : -0.5669096 
logit mean 635 : -0.4679133 
logit RMSE 635 : 0.08421564 

boosting 635 : -0.3572099 
boosting mean 635 : -0.4574423 
boosting RMSE 635 : 0.1538141 

forest 635 : -0.4357685 
forest mean 635 : -0.41611 
forest RMSE 635 : 0.05907759 

nnet 635 : -0.4897782 
nnet mean 635 : -0.3990726 
nnet RMSE 635 : 0.1477750 


s: 636 
logit 636 : -0.4427186 
logit mean 636 : -0.4678736 
logit RMSE 636 : 0.08416645 

boosting 636 : -0.2741513 
boosting mean 636 : -0.4571541 
boosting RMSE 636 : 0.1537742 

forest 636 : -0.4573458 
forest mean 636 : -0.4161748 
forest RMSE 636 : 0.05907491 

nnet 636 : -0.4182826 
nnet mean 636 : -0.3991028 
nnet RMSE 636 : 0.1476605 


s: 637 
logit 637 : -0.4357456 
logit mean 637 : -0.4678232 
logit RMSE 637 : 0.08411229 

boosting 637 : -0.4936496 
boosting mean 637 : -0.4572114 
boosting RMSE 637 : 0.1536982 

forest 637 : -0.4076419 
forest mean 637 : -0.4161614 
forest RMSE 637 : 0.0590293 

nnet 637 : -0.3787978 
nnet mean 637 : -0.3990709 
nnet RMSE 637 : 0.1475470 


s: 638 
logit 638 : -0.4671313 
logit mean 638 : -0.4678221 
logit RMSE 638 : 0.08408836 

boosting 638 : -0.5013761 
boosting mean 638 : -0.4572806 
boosting RMSE 638 : 0.1536301 

forest 638 : -0.4601192 
forest mean 638 : -0.4162303 
forest RMSE 638 : 0.05903102 

nnet 638 : -0.2737298 
nnet mean 638 : -0.3988744 
nnet RMSE 638 : 0.1475160 


s: 639 
logit 639 : -0.4799385 
logit mean 639 : -0.4678411 
logit RMSE 639 : 0.08408202 

boosting 639 : -0.5807929 
boosting mean 639 : -0.4574739 
boosting RMSE 639 : 0.1536764 

forest 639 : -0.4807895 
forest mean 639 : -0.4163314 
forest RMSE 639 : 0.05907133 

nnet 639 : -0.5318554 
nnet mean 639 : -0.3990826 
nnet RMSE 639 : 0.1474928 


s: 640 
logit 640 : -0.4335867 
logit mean 640 : -0.4677876 
logit RMSE 640 : 0.0840268 

boosting 640 : -0.4378551 
boosting mean 640 : -0.4574433 
boosting RMSE 640 : 0.1535636 

forest 640 : -0.3689395 
forest mean 640 : -0.4162573 
forest RMSE 640 : 0.05903793 

nnet 640 : -0.528987 
nnet mean 640 : -0.3992855 
nnet RMSE 640 : 0.1474657 


s: 641 
logit 641 : -0.4164321 
logit mean 641 : -0.4677074 
logit RMSE 641 : 0.08396373 

boosting 641 : -0.5579058 
boosting mean 641 : -0.4576 
boosting RMSE 641 : 0.1535705 

forest 641 : -0.5413904 
forest mean 641 : -0.4164525 
forest RMSE 641 : 0.05925561 

nnet 641 : -0.4389272 
nnet mean 641 : -0.3993474 
nnet RMSE 641 : 0.1473587 


s: 642 
logit 642 : -0.4528544 
logit mean 642 : -0.4676843 
logit RMSE 642 : 0.08392425 

boosting 642 : -0.5464306 
boosting mean 642 : -0.4577384 
boosting RMSE 642 : 0.1535596 

forest 642 : -0.4476395 
forest mean 642 : -0.4165011 
forest RMSE 642 : 0.05923929 

nnet 642 : -0.4926547 
nnet mean 642 : -0.3994927 
nnet RMSE 642 : 0.1472893 


s: 643 
logit 643 : -0.5535773 
logit mean 643 : -0.4678179 
logit RMSE 643 : 0.08407738 

boosting 643 : -0.3820986 
boosting mean 643 : -0.4576207 
boosting RMSE 643 : 0.1534418 

forest 643 : -0.3932542 
forest mean 643 : -0.4164649 
forest RMSE 643 : 0.0591938 

nnet 643 : -0.4337787 
nnet mean 643 : -0.399546 
nnet RMSE 643 : 0.1471807 


s: 644 
logit 644 : -0.4830466 
logit mean 644 : -0.4678415 
logit RMSE 644 : 0.0840758 

boosting 644 : -0.3638597 
boosting mean 644 : -0.4574751 
boosting RMSE 644 : 0.1533292 

forest 644 : -0.3711784 
forest mean 644 : -0.4163946 
forest RMSE 644 : 0.05915873 

nnet 644 : -0.002425553 
nnet mean 644 : -0.3989294 
nnet RMSE 644 : 0.1478985 


s: 645 
logit 645 : -0.3844561 
logit mean 645 : -0.4677123 
logit RMSE 645 : 0.08401282 

boosting 645 : -0.3061069 
boosting mean 645 : -0.4572405 
boosting RMSE 645 : 0.1532549 

forest 645 : -0.4245197 
forest mean 645 : -0.4164072 
forest RMSE 645 : 0.05912074 

nnet 645 : -0.1269495 
nnet mean 645 : -0.3985077 
nnet RMSE 645 : 0.1481744 


s: 646 
logit 646 : -0.4949594 
logit mean 646 : -0.4677544 
logit RMSE 646 : 0.08403087 

boosting 646 : -0.2556003 
boosting mean 646 : -0.4569283 
boosting RMSE 646 : 0.1532416 

forest 646 : -0.4129367 
forest mean 646 : -0.4164019 
forest RMSE 646 : 0.05907715 

nnet 646 : -0.3305906 
nnet mean 646 : -0.3984026 
nnet RMSE 646 : 0.1480848 


s: 647 
logit 647 : -0.4836938 
logit mean 647 : -0.4677791 
logit RMSE 647 : 0.08403035 

boosting 647 : -0.555234 
boosting mean 647 : -0.4570803 
boosting RMSE 647 : 0.1532447 

forest 647 : -0.4829384 
forest mean 647 : -0.4165047 
forest RMSE 647 : 0.05912146 

nnet 647 : -0.2495565 
nnet mean 647 : -0.3981725 
nnet RMSE 647 : 0.1480885 


s: 648 
logit 648 : -0.4755277 
logit mean 648 : -0.467791 
logit RMSE 648 : 0.08401789 

boosting 648 : -0.4709405 
boosting mean 648 : -0.4571017 
boosting RMSE 648 : 0.1531517 

forest 648 : -0.4123677 
forest mean 648 : -0.4164983 
forest RMSE 648 : 0.05907783 

nnet 648 : -0.3214466 
nnet mean 648 : -0.3980541 
nnet RMSE 648 : 0.1480064 


s: 649 
logit 649 : -0.4571006 
logit mean 649 : -0.4677746 
logit RMSE 649 : 0.08398305 

boosting 649 : -0.4523112 
boosting mean 649 : -0.4570943 
boosting RMSE 649 : 0.1530475 

forest 649 : -0.4129136 
forest mean 649 : -0.4164928 
forest RMSE 649 : 0.05903447 

nnet 649 : -0.6692163 
nnet mean 649 : -0.3984719 
nnet RMSE 649 : 0.1482694 


s: 650 
logit 650 : -0.4589573 
logit mean 650 : -0.467761 
logit RMSE 650 : 0.08395028 

boosting 650 : -0.5008786 
boosting mean 650 : -0.4571616 
boosting RMSE 650 : 0.1529809 

forest 650 : -0.4120265 
forest mean 650 : -0.4164859 
forest RMSE 650 : 0.05899093 

nnet 650 : -0.2517834 
nnet mean 650 : -0.3982463 
nnet RMSE 650 : 0.1482693 


s: 651 
logit 651 : -0.5221949 
logit mean 651 : -0.4678446 
logit RMSE 651 : 0.08402238 

boosting 651 : -0.5573345 
boosting mean 651 : -0.4573155 
boosting RMSE 651 : 0.1529877 

forest 651 : -0.4010869 
forest mean 651 : -0.4164623 
forest RMSE 651 : 0.05894562 

nnet 651 : -0.5553836 
nnet mean 651 : -0.3984876 
nnet RMSE 651 : 0.1482805 


s: 652 
logit 652 : -0.4873851 
logit mean 652 : -0.4678746 
logit RMSE 652 : 0.08402764 

boosting 652 : -0.3606385 
boosting mean 652 : -0.4571672 
boosting RMSE 652 : 0.1528781 

forest 652 : -0.3429692 
forest mean 652 : -0.4163495 
forest RMSE 652 : 0.05894273 

nnet 652 : -0.5419298 
nnet mean 652 : -0.3987076 
nnet RMSE 652 : 0.1482709 


s: 653 
logit 653 : -0.4670828 
logit mean 653 : -0.4678734 
logit RMSE 653 : 0.0840043 

boosting 653 : -0.6380484 
boosting mean 653 : -0.4574442 
boosting RMSE 653 : 0.1530448 

forest 653 : -0.5162961 
forest mean 653 : -0.4165026 
forest RMSE 653 : 0.05907315 

nnet 653 : -0.5518204 
nnet mean 653 : -0.3989421 
nnet RMSE 653 : 0.1482764 


s: 654 
logit 654 : -0.4572595 
logit mean 654 : -0.4678571 
logit RMSE 654 : 0.08396991 

boosting 654 : -0.4088497 
boosting mean 654 : -0.4573699 
boosting RMSE 654 : 0.1529281 

forest 654 : -0.4818063 
forest mean 654 : -0.4166024 
forest RMSE 654 : 0.05911458 

nnet 654 : -0.3602781 
nnet mean 654 : -0.398883 
nnet RMSE 654 : 0.1481712 


s: 655 
logit 655 : -0.5017216 
logit mean 655 : -0.4679088 
logit RMSE 655 : 0.08399987 

boosting 655 : -0.4165924 
boosting mean 655 : -0.4573077 
boosting RMSE 655 : 0.1528127 

forest 655 : -0.3672549 
forest mean 655 : -0.4165271 
forest RMSE 655 : 0.05908329 

nnet 655 : -0.326653 
nnet mean 655 : -0.3987727 
nnet RMSE 655 : 0.1480858 


s: 656 
logit 656 : -0.3864133 
logit mean 656 : -0.4677846 
logit RMSE 656 : 0.0839375 

boosting 656 : -0.3559745 
boosting mean 656 : -0.4571532 
boosting RMSE 656 : 0.1527058 

forest 656 : -0.3512088 
forest mean 656 : -0.4164275 
forest RMSE 656 : 0.05906897 

nnet 656 : -0.555672 
nnet mean 656 : -0.3990119 
nnet RMSE 656 : 0.1480976 


s: 657 
logit 657 : -0.4749777 
logit mean 657 : -0.4677956 
logit RMSE 657 : 0.08392459 

boosting 657 : -0.6631576 
boosting mean 657 : -0.4574668 
boosting RMSE 657 : 0.1529346 

forest 657 : -0.5931263 
forest mean 657 : -0.4166965 
forest RMSE 657 : 0.05950296 

nnet 657 : -0.7315189 
nnet mean 657 : -0.399518 
nnet RMSE 657 : 0.148549 


s: 658 
logit 658 : -0.4465663 
logit mean 658 : -0.4677633 
logit RMSE 658 : 0.08388044 

boosting 658 : -0.4149880 
boosting mean 658 : -0.4574022 
boosting RMSE 658 : 0.1528194 

forest 658 : -0.3722675 
forest mean 658 : -0.416629 
forest RMSE 658 : 0.05946755 

nnet 658 : -0.3846175 
nnet mean 658 : -0.3994954 
nnet RMSE 658 : 0.1484373 


s: 659 
logit 659 : -0.4598864 
logit mean 659 : -0.4677513 
logit RMSE 659 : 0.08384923 

boosting 659 : -0.6895528 
boosting mean 659 : -0.4577545 
boosting RMSE 659 : 0.1531195 

forest 659 : -0.3964398 
forest mean 659 : -0.4165983 
forest RMSE 659 : 0.05942258 

nnet 659 : -0.2580210 
nnet mean 659 : -0.3992807 
nnet RMSE 659 : 0.1484277 


s: 660 
logit 660 : -0.4755045 
logit mean 660 : -0.4677631 
logit RMSE 660 : 0.08383722 

boosting 660 : -0.3095805 
boosting mean 660 : -0.45753 
boosting RMSE 660 : 0.1530439 

forest 660 : -0.4064007 
forest mean 660 : -0.4165829 
forest RMSE 660 : 0.05937807 

nnet 660 : -0.05680324 
nnet mean 660 : -0.3987618 
nnet RMSE 660 : 0.1489156 


s: 661 
logit 661 : -0.5055403 
logit mean 661 : -0.4678202 
logit RMSE 661 : 0.08387429 

boosting 661 : -0.4742598 
boosting mean 661 : -0.4575553 
boosting RMSE 661 : 0.1529554 

forest 661 : -0.478756 
forest mean 661 : -0.4166769 
forest RMSE 661 : 0.05941216 

nnet 661 : -0.1440000 
nnet mean 661 : -0.3983763 
nnet RMSE 661 : 0.1491357 


s: 662 
logit 662 : -0.4920621 
logit mean 662 : -0.4678569 
logit RMSE 662 : 0.08388726 

boosting 662 : -0.5462572 
boosting mean 662 : -0.4576893 
boosting RMSE 662 : 0.1529455 

forest 662 : -0.4549340 
forest mean 662 : -0.4167347 
forest RMSE 662 : 0.05940565 

nnet 662 : -0.4041969 
nnet mean 662 : -0.3983851 
nnet RMSE 662 : 0.1490231 


s: 663 
logit 663 : -0.5044912 
logit mean 663 : -0.4679121 
logit RMSE 663 : 0.08392215 

boosting 663 : -0.5037554 
boosting mean 663 : -0.4577587 
boosting RMSE 663 : 0.1528832 

forest 663 : -0.4478592 
forest mean 663 : -0.4167817 
forest RMSE 663 : 0.05938992 

nnet 663 : -0.5646346 
nnet mean 663 : -0.3986359 
nnet RMSE 663 : 0.1490479 


s: 664 
logit 664 : -0.4209706 
logit mean 664 : -0.4678414 
logit RMSE 664 : 0.08386288 

boosting 664 : -0.3203055 
boosting mean 664 : -0.4575517 
boosting RMSE 664 : 0.1527993 

forest 664 : -0.4225599 
forest mean 664 : -0.4167904 
forest RMSE 664 : 0.05935164 

nnet 664 : -0.4453132 
nnet mean 664 : -0.3987062 
nnet RMSE 664 : 0.148946 


s: 665 
logit 665 : -0.3735022 
logit mean 665 : -0.4676996 
logit RMSE 665 : 0.0838061 

boosting 665 : -0.2905095 
boosting mean 665 : -0.4573005 
boosting RMSE 665 : 0.1527434 

forest 665 : -0.3313609 
forest mean 665 : -0.4166619 
forest RMSE 665 : 0.0593667 

nnet 665 : -0.5077094 
nnet mean 665 : -0.3988701 
nnet RMSE 665 : 0.1488926 


s: 666 
logit 666 : -0.4536677 
logit mean 666 : -0.4676785 
logit RMSE 666 : 0.08376898 

boosting 666 : -0.19935 
boosting mean 666 : -0.4569132 
boosting RMSE 666 : 0.1528266 

forest 666 : -0.34327 
forest mean 666 : -0.4165517 
forest RMSE 666 : 0.05936283 

nnet 666 : -0.08758593 
nnet mean 666 : -0.3984027 
nnet RMSE 666 : 0.1492724 


s: 667 
logit 667 : -0.5013352 
logit mean 667 : -0.4677289 
logit RMSE 667 : 0.08379807 

boosting 667 : -0.4154238 
boosting mean 667 : -0.456851 
boosting RMSE 667 : 0.1527132 

forest 667 : -0.3825028 
forest mean 667 : -0.4165007 
forest RMSE 667 : 0.05932218 

nnet 667 : -0.2066075 
nnet mean 667 : -0.3981152 
nnet RMSE 667 : 0.1493483 


s: 668 
logit 668 : -0.6238552 
logit mean 668 : -0.4679627 
logit RMSE 668 : 0.08418207 

boosting 668 : -0.5497721 
boosting mean 668 : -0.4569901 
boosting RMSE 668 : 0.1527088 

forest 668 : -0.4071231 
forest mean 668 : -0.4164866 
forest RMSE 668 : 0.0592784 

nnet 668 : -0.5656141 
nnet mean 668 : -0.3983659 
nnet RMSE 668 : 0.1493740 


s: 669 
logit 669 : -0.4299343 
logit mean 669 : -0.4679058 
logit RMSE 669 : 0.08412709 

boosting 669 : -0.474706 
boosting mean 669 : -0.4570166 
boosting RMSE 669 : 0.1526220 

forest 669 : -0.4084131 
forest mean 669 : -0.4164746 
forest RMSE 669 : 0.05923497 

nnet 669 : -0.3599939 
nnet mean 669 : -0.3983086 
nnet RMSE 669 : 0.1492703 


s: 670 
logit 670 : -0.5232447 
logit mean 670 : -0.4679884 
logit RMSE 670 : 0.08419902 

boosting 670 : -0.4544989 
boosting mean 670 : -0.4570129 
boosting RMSE 670 : 0.1525226 

forest 670 : -0.4051825 
forest mean 670 : -0.4164577 
forest RMSE 670 : 0.05919109 

nnet 670 : -0.6600034 
nnet mean 670 : -0.3986991 
nnet RMSE 670 : 0.1494968 


s: 671 
logit 671 : -0.4817245 
logit mean 671 : -0.4680089 
logit RMSE 671 : 0.08419538 

boosting 671 : -0.4598738 
boosting mean 671 : -0.4570171 
boosting RMSE 671 : 0.1524264 

forest 671 : -0.480719 
forest mean 671 : -0.4165535 
forest RMSE 671 : 0.059229 

nnet 671 : -0.4408266 
nnet mean 671 : -0.3987619 
nnet RMSE 671 : 0.1493936 


s: 672 
logit 672 : -0.4014841 
logit mean 672 : -0.4679099 
logit RMSE 672 : 0.08413274 

boosting 672 : -0.5299869 
boosting mean 672 : -0.4571257 
boosting RMSE 672 : 0.1523954 

forest 672 : -0.4273221 
forest mean 672 : -0.4165695 
forest RMSE 672 : 0.0591943 

nnet 672 : -0.4158144 
nnet mean 672 : -0.3987873 
nnet RMSE 672 : 0.1492837 


s: 673 
logit 673 : -0.4245944 
logit mean 673 : -0.4678455 
logit RMSE 673 : 0.08407555 

boosting 673 : -0.6010365 
boosting mean 673 : -0.4573395 
boosting RMSE 673 : 0.1524792 

forest 673 : -0.4206097 
forest mean 673 : -0.4165755 
forest RMSE 673 : 0.05915564 

nnet 673 : -0.5729158 
nnet mean 673 : -0.399046 
nnet RMSE 673 : 0.1493216 


s: 674 
logit 674 : -0.4956159 
logit mean 674 : -0.4678867 
logit RMSE 674 : 0.08409385 

boosting 674 : -0.2756549 
boosting mean 674 : -0.45707 
boosting RMSE 674 : 0.1524413 

forest 674 : -0.4708547 
forest mean 674 : -0.416656 
forest RMSE 674 : 0.05917471 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 674 : -0.3730085 
nnet mean 674 : -0.3990074 
nnet RMSE 674 : 0.1492144 


s: 675 
logit 675 : -0.4640491 
logit mean 675 : -0.4678810 
logit RMSE 675 : 0.08406769 

boosting 675 : -0.4247557 
boosting mean 675 : -0.4570221 
boosting RMSE 675 : 0.1523314 

forest 675 : -0.4939234 
forest mean 675 : -0.4167705 
forest RMSE 675 : 0.05924126 

nnet 675 : -0.3448877 
nnet mean 675 : -0.3989272 
nnet RMSE 675 : 0.1491189 


s: 676 
logit 676 : -0.5021112 
logit mean 676 : -0.4679317 
logit RMSE 676 : 0.08409724 

boosting 676 : -0.4168459 
boosting mean 676 : -0.4569627 
boosting RMSE 676 : 0.1522200 

forest 676 : -0.4352589 
forest mean 676 : -0.4167979 
forest RMSE 676 : 0.05921296 

nnet 676 : -0.4346012 
nnet mean 676 : -0.39898 
nnet RMSE 676 : 0.1490145 


s: 677 
logit 677 : -0.4744761 
logit mean 677 : -0.4679414 
logit RMSE 677 : 0.08408384 

boosting 677 : -0.419908 
boosting mean 677 : -0.4569079 
boosting RMSE 677 : 0.1521095 

forest 677 : -0.425543 
forest mean 677 : -0.4168108 
forest RMSE 677 : 0.05917736 

nnet 677 : -0.4624446 
nnet mean 677 : -0.3990737 
nnet RMSE 677 : 0.1489237 


s: 678 
logit 678 : -0.5129388 
logit mean 678 : -0.4680077 
logit RMSE 678 : 0.08413368 

boosting 678 : -0.06865953 
boosting mean 678 : -0.4563353 
boosting RMSE 678 : 0.152529 

forest 678 : -0.3686876 
forest mean 678 : -0.4167398 
forest RMSE 678 : 0.05914593 

nnet 678 : -0.3462909 
nnet mean 678 : -0.3989959 
nnet RMSE 678 : 0.1488282 


s: 679 
logit 679 : -0.4310846 
logit mean 679 : -0.4679533 
logit RMSE 679 : 0.08408017 

boosting 679 : -0.553092 
boosting mean 679 : -0.4564778 
boosting RMSE 679 : 0.1525298 

forest 679 : -0.5005118 
forest mean 679 : -0.4168632 
forest RMSE 679 : 0.0592281 

nnet 679 : -0.2745386 
nnet mean 679 : -0.3988126 
nnet RMSE 679 : 0.1487965 


s: 680 
logit 680 : -0.5028862 
logit mean 680 : -0.4680047 
logit RMSE 680 : 0.08411091 

boosting 680 : -0.3704427 
boosting mean 680 : -0.4563513 
boosting RMSE 680 : 0.1524218 

forest 680 : -0.4390942 
forest mean 680 : -0.4168959 
forest RMSE 680 : 0.05920351 

nnet 680 : -0.2074957 
nnet mean 680 : -0.3985313 
nnet RMSE 680 : 0.1488702 


s: 681 
logit 681 : -0.4305819 
logit mean 681 : -0.4679498 
logit RMSE 681 : 0.0840573 

boosting 681 : -0.4356854 
boosting mean 681 : -0.4563209 
boosting RMSE 681 : 0.1523160 

forest 681 : -0.486335 
forest mean 681 : -0.4169978 
forest RMSE 681 : 0.05925246 

nnet 681 : -0.6339156 
nnet mean 681 : -0.3988769 
nnet RMSE 681 : 0.1490306 


s: 682 
logit 682 : -0.4244053 
logit mean 682 : -0.4678859 
logit RMSE 682 : 0.08400086 

boosting 682 : -0.525624 
boosting mean 682 : -0.4564226 
boosting RMSE 682 : 0.1522803 

forest 682 : -0.3430189 
forest mean 682 : -0.4168894 
forest RMSE 682 : 0.0592492 

nnet 682 : -0.5578134 
nnet mean 682 : -0.3991099 
nnet RMSE 682 : 0.1490439 


s: 683 
logit 683 : -0.4919014 
logit mean 683 : -0.4679211 
logit RMSE 683 : 0.08401297 

boosting 683 : -0.1541346 
boosting mean 683 : -0.45598 
boosting RMSE 683 : 0.1524593 

forest 683 : -0.4241042 
forest mean 683 : -0.4168999 
forest RMSE 683 : 0.05921299 

nnet 683 : -0.4248419 
nnet mean 683 : -0.3991476 
nnet RMSE 683 : 0.1489378 


s: 684 
logit 684 : -0.4483291 
logit mean 684 : -0.4678924 
logit RMSE 684 : 0.08397187 

boosting 684 : -0.5250059 
boosting mean 684 : -0.4560809 
boosting RMSE 684 : 0.1524228 

forest 684 : -0.454095 
forest mean 684 : -0.4169543 
forest RMSE 684 : 0.05920583 

nnet 684 : -0.5311284 
nnet mean 684 : -0.3993406 
nnet RMSE 684 : 0.1489133 


s: 685 
logit 685 : -0.3964502 
logit mean 685 : -0.4677881 
logit RMSE 685 : 0.08391066 

boosting 685 : -0.2199927 
boosting mean 685 : -0.4557362 
boosting RMSE 685 : 0.1524667 

forest 685 : -0.4910485 
forest mean 685 : -0.4170625 
forest RMSE 685 : 0.05926479 

nnet 685 : -0.1004158 
nnet mean 685 : -0.3989042 
nnet RMSE 685 : 0.1492441 


s: 686 
logit 686 : -0.4486515 
logit mean 686 : -0.4677602 
logit RMSE 686 : 0.08387005 

boosting 686 : -0.3937187 
boosting mean 686 : -0.4556458 
boosting RMSE 686 : 0.1523557 

forest 686 : -0.4551402 
forest mean 686 : -0.417118 
forest RMSE 686 : 0.05925898 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 686 : -0.1743248 
nnet mean 686 : -0.3985768 
nnet RMSE 686 : 0.1493840 


s: 687 
logit 687 : -0.4650634 
logit mean 687 : -0.4677563 
logit RMSE 687 : 0.08384574 

boosting 687 : -0.1883892 
boosting mean 687 : -0.4552568 
boosting RMSE 687 : 0.1524587 

forest 687 : -0.2421450 
forest mean 687 : -0.4168633 
forest RMSE 687 : 0.05952131 

nnet 687 : -0.01592622 
nnet mean 687 : -0.3980198 
nnet RMSE 687 : 0.1499927 


s: 688 
logit 688 : -0.571802 
logit mean 688 : -0.4679075 
logit RMSE 688 : 0.08404041 

boosting 688 : -0.4699483 
boosting mean 688 : -0.4552782 
boosting RMSE 688 : 0.1523712 

forest 688 : -0.3933583 
forest mean 688 : -0.4168291 
forest RMSE 688 : 0.05947858 

nnet 688 : -0.472078 
nnet mean 688 : -0.3981275 
nnet RMSE 688 : 0.1499089 


s: 689 
logit 689 : -0.495014 
logit mean 689 : -0.4679469 
logit RMSE 689 : 0.08405738 

boosting 689 : -0.5813643 
boosting mean 689 : -0.4554612 
boosting RMSE 689 : 0.1524173 

forest 689 : -0.5085824 
forest mean 689 : -0.4169623 
forest RMSE 689 : 0.05957918 

nnet 689 : -0.478066 
nnet mean 689 : -0.3982435 
nnet RMSE 689 : 0.1498296 


s: 690 
logit 690 : -0.3334175 
logit mean 690 : -0.4677519 
logit RMSE 690 : 0.08403468 

boosting 690 : -0.4765070 
boosting mean 690 : -0.4554917 
boosting RMSE 690 : 0.1523347 

forest 690 : -0.4796317 
forest mean 690 : -0.4170531 
forest RMSE 690 : 0.05961312 

nnet 690 : -0.2307936 
nnet mean 690 : -0.3980008 
nnet RMSE 690 : 0.1498595 


s: 691 
logit 691 : -0.504934 
logit mean 691 : -0.4678057 
logit RMSE 691 : 0.08406868 

boosting 691 : -0.4007469 
boosting mean 691 : -0.4554124 
boosting RMSE 691 : 0.1522244 

forest 691 : -0.4166285 
forest mean 691 : -0.4170525 
forest RMSE 691 : 0.05957333 

nnet 691 : -0.3380516 
nnet mean 691 : -0.3979140 
nnet RMSE 691 : 0.1497695 


s: 692 
logit 692 : -0.4502005 
logit mean 692 : -0.4677803 
logit RMSE 692 : 0.08402959 

boosting 692 : -0.6174914 
boosting mean 692 : -0.4556466 
boosting RMSE 692 : 0.1523389 

forest 692 : -0.3912178 
forest mean 692 : -0.4170152 
forest RMSE 692 : 0.05953121 

nnet 692 : -0.3995960 
nnet mean 692 : -0.3979165 
nnet RMSE 692 : 0.1496613 


s: 693 
logit 693 : -0.57077 
logit mean 693 : -0.4679289 
logit RMSE 693 : 0.08421914 

boosting 693 : -0.4716326 
boosting mean 693 : -0.4556697 
boosting RMSE 693 : 0.1522533 

forest 693 : -0.524915 
forest mean 693 : -0.4171709 
forest RMSE 693 : 0.05967719 

nnet 693 : -0.2670875 
nnet mean 693 : -0.3977277 
nnet RMSE 693 : 0.1496385 


s: 694 
logit 694 : -0.5022268 
logit mean 694 : -0.4679783 
logit RMSE 694 : 0.08424786 

boosting 694 : -0.6129895 
boosting mean 694 : -0.4558964 
boosting RMSE 694 : 0.1523582 

forest 694 : -0.4261249 
forest mean 694 : -0.4171838 
forest RMSE 694 : 0.05964242 

nnet 694 : -0.4322933 
nnet mean 694 : -0.3977775 
nnet RMSE 694 : 0.1495357 


s: 695 
logit 695 : -0.4415121 
logit mean 695 : -0.4679402 
logit RMSE 695 : 0.08420195 

boosting 695 : -0.6072965 
boosting mean 695 : -0.4561142 
boosting RMSE 695 : 0.1524515 

forest 695 : -0.4263302 
forest mean 695 : -0.4171969 
forest RMSE 695 : 0.05960787 

nnet 695 : -0.3861847 
nnet mean 695 : -0.3977608 
nnet RMSE 695 : 0.1494290 


s: 696 
logit 696 : -0.4794459 
logit mean 696 : -0.4679568 
logit RMSE 696 : 0.08419531 

boosting 696 : -0.554531 
boosting mean 696 : -0.4562556 
boosting RMSE 696 : 0.1524545 

forest 696 : -0.4053564 
forest mean 696 : -0.4171799 
forest RMSE 696 : 0.05956538 

nnet 696 : -0.6118938 
nnet mean 696 : -0.3980685 
nnet RMSE 696 : 0.1495374 


s: 697 
logit 697 : -0.4051186 
logit mean 697 : -0.4678666 
logit RMSE 697 : 0.08413512 

boosting 697 : -0.5722736 
boosting mean 697 : -0.4564221 
boosting RMSE 697 : 0.1524848 

forest 697 : -0.4661275 
forest mean 697 : -0.4172501 
forest RMSE 697 : 0.05957531 

nnet 697 : -0.48816 
nnet mean 697 : -0.3981977 
nnet RMSE 697 : 0.1494674 


s: 698 
logit 698 : -0.3710417 
logit mean 698 : -0.4677279 
logit RMSE 698 : 0.08408197 

boosting 698 : -0.5076429 
boosting mean 698 : -0.4564955 
boosting RMSE 698 : 0.1524299 

forest 698 : -0.4314357 
forest mean 698 : -0.4172705 
forest RMSE 698 : 0.05954451 

nnet 698 : -0.450603 
nnet mean 698 : -0.3982728 
nnet RMSE 698 : 0.1493726 


s: 699 
logit 699 : -0.455883 
logit mean 699 : -0.4677110 
logit RMSE 699 : 0.08404839 

boosting 699 : -0.4335307 
boosting mean 699 : -0.4564626 
boosting RMSE 699 : 0.1523262 

forest 699 : -0.4217084 
forest mean 699 : -0.4172768 
forest RMSE 699 : 0.05950756 

nnet 699 : -0.5078317 
nnet mean 699 : -0.3984296 
nnet RMSE 699 : 0.1493214 


s: 700 
logit 700 : -0.3863675 
logit mean 700 : -0.4675947 
logit RMSE 700 : 0.08398991 

boosting 700 : -0.4488888 
boosting mean 700 : -0.4564518 
boosting RMSE 700 : 0.1522285 

forest 700 : -0.3692751 
forest mean 700 : -0.4172082 
forest RMSE 700 : 0.05947638 

nnet 700 : -0.5257161 
nnet mean 700 : -0.3986114 
nnet RMSE 700 : 0.1492904 


s: 701 
logit 701 : -0.3863764 
logit mean 701 : -0.4674789 
logit RMSE 701 : 0.08393156 

boosting 701 : -0.5780834 
boosting mean 701 : -0.4566253 
boosting RMSE 701 : 0.1522685 

forest 701 : -0.4000156 
forest mean 701 : -0.4171837 
forest RMSE 701 : 0.05943394 

nnet 701 : -0.4887513 
nnet mean 701 : -0.39874 
nnet RMSE 701 : 0.1492215 


s: 702 
logit 702 : -0.4602219 
logit mean 702 : -0.4674685 
logit RMSE 702 : 0.08390255 

boosting 702 : -0.4333310 
boosting mean 702 : -0.4565921 
boosting RMSE 702 : 0.1521652 

forest 702 : -0.4354371 
forest mean 702 : -0.4172097 
forest RMSE 702 : 0.05940666 

nnet 702 : -0.1891332 
nnet mean 702 : -0.3984414 
nnet RMSE 702 : 0.1493274 


s: 703 
logit 703 : -0.4908843 
logit mean 703 : -0.4675019 
logit RMSE 703 : 0.0839129 

boosting 703 : -0.8281371 
boosting mean 703 : -0.4571206 
boosting RMSE 703 : 0.1529120 

forest 703 : -0.5350367 
forest mean 703 : -0.4173773 
forest RMSE 703 : 0.05958246 

nnet 703 : -0.2687525 
nnet mean 703 : -0.3982569 
nnet RMSE 703 : 0.1493032 


s: 704 
logit 704 : -0.4905318 
logit mean 704 : -0.4675346 
logit RMSE 704 : 0.08392267 

boosting 704 : -0.2720753 
boosting mean 704 : -0.4568578 
boosting RMSE 704 : 0.1528794 

forest 704 : -0.4432538 
forest mean 704 : -0.4174141 
forest RMSE 704 : 0.05956244 

nnet 704 : -0.4330432 
nnet mean 704 : -0.3983063 
nnet RMSE 704 : 0.1492024 


s: 705 
logit 705 : -0.4599711 
logit mean 705 : -0.4675238 
logit RMSE 705 : 0.08389354 

boosting 705 : -0.6809504 
boosting mean 705 : -0.4571757 
boosting RMSE 705 : 0.1531369 

forest 705 : -0.4864701 
forest mean 705 : -0.417512 
forest RMSE 705 : 0.05960921 

nnet 705 : -0.5481181 
nnet mean 705 : -0.3985188 
nnet RMSE 705 : 0.1492008 


s: 706 
logit 706 : -0.39623 
logit mean 706 : -0.4674229 
logit RMSE 706 : 0.08383422 

boosting 706 : -0.6153881 
boosting mean 706 : -0.4573998 
boosting RMSE 706 : 0.1532430 

forest 706 : -0.4237455 
forest mean 706 : -0.4175209 
forest RMSE 706 : 0.05957368 

nnet 706 : -0.6140035 
nnet mean 706 : -0.3988240 
nnet RMSE 706 : 0.1493125 


s: 707 
logit 707 : -0.3911443 
logit mean 707 : -0.467315 
logit RMSE 707 : 0.08377557 

boosting 707 : -0.714753 
boosting mean 707 : -0.4577638 
boosting RMSE 707 : 0.1535914 

forest 707 : -0.4244973 
forest mean 707 : -0.4175307 
forest RMSE 707 : 0.05953866 

nnet 707 : -0.4063072 
nnet mean 707 : -0.3988346 
nnet RMSE 707 : 0.1492071 


s: 708 
logit 708 : -0.4559191 
logit mean 708 : -0.4672989 
logit RMSE 708 : 0.08374276 

boosting 708 : -0.1066520 
boosting mean 708 : -0.4572678 
boosting RMSE 708 : 0.1538783 

forest 708 : -0.3589811 
forest mean 708 : -0.417448 
forest RMSE 708 : 0.05951657 

nnet 708 : -0.4161406 
nnet mean 708 : -0.3988591 
nnet RMSE 708 : 0.1491029 


s: 709 
logit 709 : -0.4351174 
logit mean 709 : -0.4672535 
logit RMSE 709 : 0.08369408 

boosting 709 : -0.3719142 
boosting mean 709 : -0.4571475 
boosting RMSE 709 : 0.1537734 

forest 709 : -0.4620164 
forest mean 709 : -0.4175109 
forest RMSE 709 : 0.05952017 

nnet 709 : -0.4590577 
nnet mean 709 : -0.398944 
nnet RMSE 709 : 0.1490142 


s: 710 
logit 710 : -0.549419 
logit mean 710 : -0.4673692 
logit RMSE 710 : 0.0838229 

boosting 710 : -0.5178458 
boosting mean 710 : -0.4572330 
boosting RMSE 710 : 0.1537287 

forest 710 : -0.4330867 
forest mean 710 : -0.4175328 
forest RMSE 710 : 0.0594912 

nnet 710 : -0.3434602 
nnet mean 710 : -0.3988658 
nnet RMSE 710 : 0.1489243 


s: 711 
logit 711 : -0.4465774 
logit mean 711 : -0.46734 
logit RMSE 711 : 0.08378214 

boosting 711 : -0.4101344 
boosting mean 711 : -0.4571667 
boosting RMSE 711 : 0.153621 

forest 711 : -0.4265987 
forest mean 711 : -0.4175456 
forest RMSE 711 : 0.05945772 

nnet 711 : -0.5078531 
nnet mean 711 : -0.3990191 
nnet RMSE 711 : 0.1488745 


s: 712 
logit 712 : -0.5802578 
logit mean 712 : -0.4674986 
logit RMSE 712 : 0.08399538 

boosting 712 : -0.7371223 
boosting mean 712 : -0.4575599 
boosting RMSE 712 : 0.1540321 

forest 712 : -0.4104989 
forest mean 712 : -0.4175357 
forest RMSE 712 : 0.05941725 

nnet 712 : -0.5269123 
nnet mean 712 : -0.3991987 
nnet RMSE 712 : 0.1488460 


s: 713 
logit 713 : -0.4374001 
logit mean 713 : -0.4674563 
logit RMSE 713 : 0.08394814 

boosting 713 : -0.04184831 
boosting mean 713 : -0.4569769 
boosting RMSE 713 : 0.1545074 

forest 713 : -0.3519571 
forest mean 713 : -0.4174437 
forest RMSE 713 : 0.05940282 

nnet 713 : -0.3582233 
nnet mean 713 : -0.3991413 
nnet RMSE 713 : 0.1487498 


s: 714 
logit 714 : -0.5040902 
logit mean 714 : -0.4675077 
logit RMSE 714 : 0.08397973 

boosting 714 : -0.5056305 
boosting mean 714 : -0.457045 
boosting RMSE 714 : 0.1544497 

forest 714 : -0.4660779 
forest mean 714 : -0.4175118 
forest RMSE 714 : 0.0594127 

nnet 714 : -0.4328032 
nnet mean 714 : -0.3991884 
nnet RMSE 714 : 0.1486506 


s: 715 
logit 715 : -0.5053217 
logit mean 715 : -0.4675605 
logit RMSE 715 : 0.08401337 

boosting 715 : -0.4091719 
boosting mean 715 : -0.456978 
boosting RMSE 715 : 0.1543421 

forest 715 : -0.5041184 
forest mean 715 : -0.4176329 
forest RMSE 715 : 0.05949868 

nnet 715 : -0.3766578 
nnet mean 715 : -0.3991569 
nnet RMSE 715 : 0.1485492 


s: 716 
logit 716 : -0.5366104 
logit mean 716 : -0.467657 
logit RMSE 716 : 0.08410977 

boosting 716 : -0.4325655 
boosting mean 716 : -0.4569439 
boosting RMSE 716 : 0.1542390 

forest 716 : -0.43456 
forest mean 716 : -0.4176566 
forest RMSE 716 : 0.05947115 

nnet 716 : -0.4426602 
nnet mean 716 : -0.3992177 
nnet RMSE 716 : 0.148454 


s: 717 
logit 717 : -0.5361999 
logit mean 717 : -0.4677526 
logit RMSE 717 : 0.08420486 

boosting 717 : -0.1575174 
boosting mean 717 : -0.4565263 
boosting RMSE 717 : 0.1543972 

forest 717 : -0.341756 
forest mean 717 : -0.4175507 
forest RMSE 717 : 0.05946945 

nnet 717 : -0.2983659 
nnet mean 717 : -0.399077 
nnet RMSE 717 : 0.148399 


s: 718 
logit 718 : -0.5365668 
logit mean 718 : -0.4678484 
logit RMSE 718 : 0.0843004 

boosting 718 : -0.5240593 
boosting mean 718 : -0.4566204 
boosting RMSE 718 : 0.1543591 

forest 718 : -0.4158284 
forest mean 718 : -0.4175483 
forest RMSE 718 : 0.05943096 

nnet 718 : -0.3820908 
nnet mean 718 : -0.3990534 
nnet RMSE 718 : 0.1482971 


s: 719 
logit 719 : -0.4726901 
logit mean 719 : -0.4678551 
logit RMSE 719 : 0.08428537 

boosting 719 : -0.4044742 
boosting mean 719 : -0.4565479 
boosting RMSE 719 : 0.1542518 

forest 719 : -0.4275261 
forest mean 719 : -0.4175622 
forest RMSE 719 : 0.05939849 

nnet 719 : -0.2370773 
nnet mean 719 : -0.3988281 
nnet RMSE 719 : 0.1483185 


s: 720 
logit 720 : -0.526929 
logit mean 720 : -0.4679372 
logit RMSE 720 : 0.08435955 

boosting 720 : -0.392484 
boosting mean 720 : -0.4564589 
boosting RMSE 720 : 0.1541449 

forest 720 : -0.4895215 
forest mean 720 : -0.4176621 
forest RMSE 720 : 0.05945091 

nnet 720 : -0.5123274 
nnet mean 720 : -0.3989857 
nnet RMSE 720 : 0.1482745 


s: 721 
logit 721 : -0.5224054 
logit mean 721 : -0.4680127 
logit RMSE 721 : 0.08442419 

boosting 721 : -0.3896065 
boosting mean 721 : -0.4563662 
boosting RMSE 721 : 0.1540385 

forest 721 : -0.536765 
forest mean 721 : -0.4178273 
forest RMSE 721 : 0.05962761 

nnet 721 : -0.6731899 
nnet mean 721 : -0.399366 
nnet RMSE 721 : 0.1485206 


s: 722 
logit 722 : -0.4159067 
logit mean 722 : -0.4679406 
logit RMSE 722 : 0.08436778 

boosting 722 : -0.7215398 
boosting mean 722 : -0.4567334 
boosting RMSE 722 : 0.1543962 

forest 722 : -0.4247435 
forest mean 722 : -0.4178369 
forest RMSE 722 : 0.05959341 

nnet 722 : -0.5936476 
nnet mean 722 : -0.3996351 
nnet RMSE 722 : 0.1485925 


s: 723 
logit 723 : -0.4358648 
logit mean 723 : -0.4678962 
logit RMSE 723 : 0.08431996 

boosting 723 : -0.509686 
boosting mean 723 : -0.4568067 
boosting RMSE 723 : 0.1543433 

forest 723 : -0.3583795 
forest mean 723 : -0.4177547 
forest RMSE 723 : 0.0595723 

nnet 723 : -0.4798237 
nnet mean 723 : -0.399746 
nnet RMSE 723 : 0.1485194 


s: 724 
logit 724 : -0.4606407 
logit mean 724 : -0.4678862 
logit RMSE 724 : 0.08429185 

boosting 724 : -0.6066809 
boosting mean 724 : -0.4570137 
boosting RMSE 724 : 0.1544278 

forest 724 : -0.4438467 
forest mean 724 : -0.4177907 
forest RMSE 724 : 0.05955344 

nnet 724 : -0.5314243 
nnet mean 724 : -0.3999279 
nnet RMSE 724 : 0.1484972 


s: 725 
logit 725 : -0.5450575 
logit mean 725 : -0.4679926 
logit RMSE 725 : 0.0844058 

boosting 725 : -0.6266194 
boosting mean 725 : -0.4572476 
boosting RMSE 725 : 0.1545506 

forest 725 : -0.3910614 
forest mean 725 : -0.4177539 
forest RMSE 725 : 0.05951328 

nnet 725 : -0.606615 
nnet mean 725 : -0.400213 
nnet RMSE 725 : 0.148593 


s: 726 
logit 726 : -0.4623028 
logit mean 726 : -0.4679848 
logit RMSE 726 : 0.08437933 

boosting 726 : -0.3264209 
boosting mean 726 : -0.4570674 
boosting RMSE 726 : 0.1544683 

forest 726 : -0.4253442 
forest mean 726 : -0.4177643 
forest RMSE 726 : 0.05947972 

nnet 726 : -0.5494759 
nnet mean 726 : -0.4004186 
nnet RMSE 726 : 0.1485942 


s: 727 
logit 727 : -0.4029279 
logit mean 727 : -0.4678953 
logit RMSE 727 : 0.08432135 

boosting 727 : -0.461311 
boosting mean 727 : -0.4570733 
boosting RMSE 727 : 0.1543788 

forest 727 : -0.4141248 
forest mean 727 : -0.4177593 
forest RMSE 727 : 0.05944111 

nnet 727 : -0.3743260 
nnet mean 727 : -0.4003827 
nnet RMSE 727 : 0.1484950 


s: 728 
logit 728 : -0.5137555 
logit mean 728 : -0.4679583 
logit RMSE 728 : 0.08436882 

boosting 728 : -0.406557 
boosting mean 728 : -0.4570039 
boosting RMSE 728 : 0.1542729 

forest 728 : -0.4008481 
forest mean 728 : -0.4177361 
forest RMSE 728 : 0.05940028 

nnet 728 : -0.4482012 
nnet mean 728 : -0.4004484 
nnet RMSE 728 : 0.1484038 


s: 729 
logit 729 : -0.4129502 
logit mean 729 : -0.4678828 
logit RMSE 729 : 0.0843123 

boosting 729 : -0.4716631 
boosting mean 729 : -0.457024 
boosting RMSE 729 : 0.1541899 

forest 729 : -0.4294885 
forest mean 729 : -0.4177522 
forest RMSE 729 : 0.05936957 

nnet 729 : -0.4244589 
nnet mean 729 : -0.4004813 
nnet RMSE 729 : 0.1483047 


s: 730 
logit 730 : -0.4653416 
logit mean 730 : -0.4678794 
logit RMSE 730 : 0.08428924 

boosting 730 : -0.4226536 
boosting mean 730 : -0.4569769 
boosting RMSE 730 : 0.1540865 

forest 730 : -0.4933597 
forest mean 730 : -0.4178558 
forest RMSE 730 : 0.05942943 

nnet 730 : -0.2923624 
nnet mean 730 : -0.4003332 
nnet RMSE 730 : 0.1482566 


s: 731 
logit 731 : -0.4345797 
logit mean 731 : -0.4678338 
logit RMSE 731 : 0.08424127 

boosting 731 : -0.3966912 
boosting mean 731 : -0.4568944 
boosting RMSE 731 : 0.1539812 

forest 731 : -0.3911941 
forest mean 731 : -0.4178193 
forest RMSE 731 : 0.05938966 

nnet 731 : -0.4650562 
nnet mean 731 : -0.4004217 
nnet RMSE 731 : 0.1481747 


s: 732 
logit 732 : -0.4588066 
logit mean 732 : -0.4678215 
logit RMSE 732 : 0.08421177 

boosting 732 : -0.4321176 
boosting mean 732 : -0.4568606 
boosting RMSE 732 : 0.1538805 

forest 732 : -0.4212189 
forest mean 732 : -0.4178239 
forest RMSE 732 : 0.05935426 

nnet 732 : -0.5391049 
nnet mean 732 : -0.4006112 
nnet RMSE 732 : 0.1481627 


s: 733 
logit 733 : -0.4563775 
logit mean 733 : -0.4678059 
logit RMSE 733 : 0.08418006 

boosting 733 : -0.5608296 
boosting mean 733 : -0.4570024 
boosting RMSE 733 : 0.1538902 

forest 733 : -0.427878 
forest mean 733 : -0.4178377 
forest RMSE 733 : 0.0593227 

nnet 733 : -0.3995077 
nnet mean 733 : -0.4006097 
nnet RMSE 733 : 0.1480616 


s: 734 
logit 734 : -0.5010248 
logit mean 734 : -0.4678511 
logit RMSE 734 : 0.0842053 

boosting 734 : -0.4506725 
boosting mean 734 : -0.4569938 
boosting RMSE 734 : 0.1537967 

forest 734 : -0.4253932 
forest mean 734 : -0.4178479 
forest RMSE 734 : 0.05928968 

nnet 734 : -1.028300 
nnet mean 734 : -0.4014649 
nnet RMSE 734 : 0.1497671 


s: 735 
logit 735 : -0.4056837 
logit mean 735 : -0.4677665 
logit RMSE 735 : 0.08414826 

boosting 735 : -0.8043974 
boosting mean 735 : -0.4574665 
boosting RMSE 735 : 0.1544142 

forest 735 : -0.4685842 
forest mean 735 : -0.417917 
forest RMSE 735 : 0.05930331 

nnet 735 : -0.3565831 
nnet mean 735 : -0.4014038 
nnet RMSE 735 : 0.1496738 


s: 736 
logit 736 : -0.459901 
logit mean 736 : -0.4677559 
logit RMSE 736 : 0.08412006 

boosting 736 : -0.458426 
boosting mean 736 : -0.4574678 
boosting RMSE 736 : 0.1543243 

forest 736 : -0.4622623 
forest mean 736 : -0.4179772 
forest RMSE 736 : 0.05930744 

nnet 736 : -0.2583693 
nnet mean 736 : -0.4012095 
nnet RMSE 736 : 0.1496632 


s: 737 
logit 737 : -0.4742705 
logit mean 737 : -0.4677647 
logit RMSE 737 : 0.08410748 

boosting 737 : -0.436408 
boosting mean 737 : -0.4574392 
boosting RMSE 737 : 0.1542254 

forest 737 : -0.5095669 
forest mean 737 : -0.4181015 
forest RMSE 737 : 0.05940445 

nnet 737 : -0.2293545 
nnet mean 737 : -0.4009763 
nnet RMSE 737 : 0.1496936 


s: 738 
logit 738 : -0.5022253 
logit mean 738 : -0.4678114 
logit RMSE 738 : 0.08413467 

boosting 738 : -0.4416442 
boosting mean 738 : -0.4574178 
boosting RMSE 738 : 0.1541285 

forest 738 : -0.4922604 
forest mean 738 : -0.418202 
forest RMSE 738 : 0.05946125 

nnet 738 : -0.3956188 
nnet mean 738 : -0.400969 
nnet RMSE 738 : 0.1495923 


s: 739 
logit 739 : -0.3983652 
logit mean 739 : -0.4677174 
logit RMSE 739 : 0.08407774 

boosting 739 : -0.3962426 
boosting mean 739 : -0.457335 
boosting RMSE 739 : 0.1540242 

forest 739 : -0.3685225 
forest mean 739 : -0.4181348 
forest RMSE 739 : 0.05943229 

nnet 739 : -0.302674 
nnet mean 739 : -0.400836 
nnet RMSE 739 : 0.1495339 


s: 740 
logit 740 : -0.5277817 
logit mean 740 : -0.4677986 
logit RMSE 740 : 0.08415212 

boosting 740 : -0.3781477 
boosting mean 740 : -0.457228 
boosting RMSE 740 : 0.1539222 

forest 740 : -0.4309346 
forest mean 740 : -0.4181521 
forest RMSE 740 : 0.059403 

nnet 740 : -0.3980457 
nnet mean 740 : -0.4008322 
nnet RMSE 740 : 0.1494328 


s: 741 
logit 741 : -0.4837934 
logit mean 741 : -0.4678202 
logit RMSE 741 : 0.08415164 

boosting 741 : -0.4615126 
boosting mean 741 : -0.4572338 
boosting RMSE 741 : 0.1538349 

forest 741 : -0.4834059 
forest mean 741 : -0.4182401 
forest RMSE 741 : 0.05944193 

nnet 741 : -0.4156984 
nnet mean 741 : -0.4008523 
nnet RMSE 741 : 0.1493331 


s: 742 
logit 742 : -0.4407909 
logit mean 742 : -0.4677837 
logit RMSE 742 : 0.08410824 

boosting 742 : -0.2513965 
boosting mean 742 : -0.4569564 
boosting RMSE 742 : 0.153828 

forest 742 : -0.4394656 
forest mean 742 : -0.4182687 
forest RMSE 742 : 0.05941952 

nnet 742 : -0.353987 
nnet mean 742 : -0.4007891 
nnet RMSE 742 : 0.1492420 


s: 743 
logit 743 : -0.4435844 
logit mean 743 : -0.4677512 
logit RMSE 743 : 0.08406683 

boosting 743 : -0.1947155 
boosting mean 743 : -0.4566034 
boosting RMSE 743 : 0.1539088 

forest 743 : -0.4935526 
forest mean 743 : -0.4183700 
forest RMSE 743 : 0.05947863 

nnet 743 : -0.5998807 
nnet mean 743 : -0.4010571 
nnet RMSE 743 : 0.1493217 


s: 744 
logit 744 : -0.4434247 
logit mean 744 : -0.4677185 
logit RMSE 744 : 0.0840254 

boosting 744 : -0.467322 
boosting mean 744 : -0.4566178 
boosting RMSE 744 : 0.1538252 

forest 744 : -0.4393603 
forest mean 744 : -0.4183983 
forest RMSE 744 : 0.05945616 

nnet 744 : -0.3171098 
nnet mean 744 : -0.4009443 
nnet RMSE 744 : 0.1492522 


s: 745 
logit 745 : -0.4525452 
logit mean 745 : -0.4676981 
logit RMSE 745 : 0.08399105 

boosting 745 : -0.378138 
boosting mean 745 : -0.4565125 
boosting RMSE 745 : 0.1537240 

forest 745 : -0.4205154 
forest mean 745 : -0.4184011 
forest RMSE 745 : 0.059421 

nnet 745 : -0.2415533 
nnet mean 745 : -0.4007303 
nnet RMSE 745 : 0.1492649 


s: 746 
logit 746 : -0.4634939 
logit mean 746 : -0.4676925 
logit RMSE 746 : 0.08396693 

boosting 746 : -0.4222393 
boosting mean 746 : -0.4564665 
boosting RMSE 746 : 0.1536231 

forest 746 : -0.4112902 
forest mean 746 : -0.4183916 
forest RMSE 746 : 0.05938259 

nnet 746 : -0.2178067 
nnet mean 746 : -0.4004851 
nnet RMSE 746 : 0.1493139 


s: 747 
logit 747 : -0.5259437 
logit mean 747 : -0.4677704 
logit RMSE 747 : 0.08403714 

boosting 747 : -0.3566324 
boosting mean 747 : -0.4563329 
boosting RMSE 747 : 0.1535284 

forest 747 : -0.4080745 
forest mean 747 : -0.4183778 
forest RMSE 747 : 0.05934357 

nnet 747 : -0.3011446 
nnet mean 747 : -0.4003521 
nnet RMSE 747 : 0.1492578 


s: 748 
logit 748 : -0.5000568 
logit mean 748 : -0.4678136 
logit RMSE 748 : 0.0840606 

boosting 748 : -0.5719213 
boosting mean 748 : -0.4564874 
boosting RMSE 748 : 0.1535545 

forest 748 : -0.4199030 
forest mean 748 : -0.4183798 
forest RMSE 748 : 0.05930835 

nnet 748 : -0.3126967 
nnet mean 748 : -0.4002349 
nnet RMSE 748 : 0.1491921 


s: 749 
logit 749 : -0.46852 
logit mean 749 : -0.4678146 
logit RMSE 749 : 0.08404176 

boosting 749 : -0.8227832 
boosting mean 749 : -0.4569765 
boosting RMSE 749 : 0.1542275 

forest 749 : -0.457363 
forest mean 749 : -0.4184318 
forest RMSE 749 : 0.0593058 

nnet 749 : -0.3993559 
nnet mean 749 : -0.4002338 
nnet RMSE 749 : 0.1490925 


s: 750 
logit 750 : -0.4068448 
logit mean 750 : -0.4677333 
logit RMSE 750 : 0.08398608 

boosting 750 : -0.4162672 
boosting mean 750 : -0.4569222 
boosting RMSE 750 : 0.1541258 

forest 750 : -0.3705511 
forest mean 750 : -0.418368 
forest RMSE 750 : 0.059276 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 750 : -0.3013937 
nnet mean 750 : -0.400102 
nnet RMSE 750 : 0.1490366 


s: 751 
logit 751 : -0.4189189 
logit mean 751 : -0.4676683 
logit RMSE 751 : 0.08393299 

boosting 751 : -0.4015566 
boosting mean 751 : -0.4568485 
boosting RMSE 751 : 0.1540232 

forest 751 : -0.4596616 
forest mean 751 : -0.418423 
forest RMSE 751 : 0.05927652 

nnet 751 : -0.3714339 
nnet mean 751 : -0.4000638 
nnet RMSE 751 : 0.1489410 


s: 752 
logit 752 : -0.4484472 
logit mean 752 : -0.4676427 
logit RMSE 752 : 0.08389577 

boosting 752 : -0.5132043 
boosting mean 752 : -0.4569234 
boosting RMSE 752 : 0.1539761 

forest 752 : -0.4425425 
forest mean 752 : -0.4184551 
forest RMSE 752 : 0.0592574 

nnet 752 : -0.270966 
nnet mean 752 : -0.3998921 
nnet RMSE 752 : 0.1489163 


s: 753 
logit 753 : -0.4458829 
logit mean 753 : -0.4676138 
logit RMSE 753 : 0.08385671 

boosting 753 : -0.4058161 
boosting mean 753 : -0.4568555 
boosting RMSE 753 : 0.1538740 

forest 753 : -0.541182 
forest mean 753 : -0.4186180 
forest RMSE 753 : 0.05944112 

nnet 753 : -0.3396139 
nnet mean 753 : -0.3998121 
nnet RMSE 753 : 0.1488336 


s: 754 
logit 754 : -0.5887241 
logit mean 754 : -0.4677744 
logit RMSE 754 : 0.08408246 

boosting 754 : -0.5321674 
boosting mean 754 : -0.4569554 
boosting RMSE 754 : 0.1538472 

forest 754 : -0.3875393 
forest mean 754 : -0.4185768 
forest RMSE 754 : 0.05940342 

nnet 754 : -0.5395683 
nnet mean 754 : -0.3999974 
nnet RMSE 754 : 0.1488217 


s: 755 
logit 755 : -0.5568773 
logit mean 755 : -0.4678924 
logit RMSE 755 : 0.0842205 

boosting 755 : -0.5906493 
boosting mean 755 : -0.4571325 
boosting RMSE 755 : 0.1539018 

forest 755 : -0.4032997 
forest mean 755 : -0.4185566 
forest RMSE 755 : 0.05936419 

nnet 755 : -0.3932191 
nnet mean 755 : -0.3999884 
nnet RMSE 755 : 0.1487233 


s: 756 
logit 756 : -0.4523571 
logit mean 756 : -0.4678719 
logit RMSE 756 : 0.08418631 

boosting 756 : -0.6309171 
boosting mean 756 : -0.4573624 
boosting RMSE 756 : 0.1540291 

forest 756 : -0.3827526 
forest mean 756 : -0.4185092 
forest RMSE 756 : 0.05932823 

nnet 756 : -0.2922042 
nnet mean 756 : -0.3998459 
nnet RMSE 756 : 0.1486766 


s: 757 
logit 757 : -0.4279031 
logit mean 757 : -0.4678191 
logit RMSE 757 : 0.0841368 

boosting 757 : -0.6898325 
boosting mean 757 : -0.4576695 
boosting RMSE 757 : 0.1542874 

forest 757 : -0.5367043 
forest mean 757 : -0.4186654 
forest RMSE 757 : 0.05949686 

nnet 757 : -0.2508834 
nnet mean 757 : -0.3996491 
nnet RMSE 757 : 0.1486772 


s: 758 
logit 758 : -0.5771711 
logit mean 758 : -0.4679634 
logit RMSE 758 : 0.08432718 

boosting 758 : -0.597674 
boosting mean 758 : -0.4578542 
boosting RMSE 758 : 0.1543526 

forest 758 : -0.3976293 
forest mean 758 : -0.4186376 
forest RMSE 758 : 0.05945767 

nnet 758 : -0.3463972 
nnet mean 758 : -0.3995788 
nnet RMSE 758 : 0.1485919 


s: 759 
logit 759 : -0.4507154 
logit mean 759 : -0.4679406 
logit RMSE 759 : 0.08429172 

boosting 759 : -0.5440433 
boosting mean 759 : -0.4579677 
boosting RMSE 759 : 0.1543395 

forest 759 : -0.42342 
forest mean 759 : -0.4186439 
forest RMSE 759 : 0.05942457 

nnet 759 : -0.6164151 
nnet mean 759 : -0.3998645 
nnet RMSE 759 : 0.1487016 


s: 760 
logit 760 : -0.5847444 
logit mean 760 : -0.4680943 
logit RMSE 760 : 0.08450239 

boosting 760 : -0.6287848 
boosting mean 760 : -0.4581925 
boosting RMSE 760 : 0.1544610 

forest 760 : -0.401553 
forest mean 760 : -0.4186214 
forest RMSE 760 : 0.05938548 

nnet 760 : -0.4890952 
nnet mean 760 : -0.3999819 
nnet RMSE 760 : 0.1486389 


s: 761 
logit 761 : -0.4428338 
logit mean 761 : -0.4680611 
logit RMSE 761 : 0.08446112 

boosting 761 : -0.6588235 
boosting mean 761 : -0.4584561 
boosting RMSE 761 : 0.1546444 

forest 761 : -0.3453158 
forest mean 761 : -0.4185251 
forest RMSE 761 : 0.05937955 

nnet 761 : -0.3300621 
nnet mean 761 : -0.3998901 
nnet RMSE 761 : 0.1485628 


s: 762 
logit 762 : -0.4402714 
logit mean 762 : -0.4680247 
logit RMSE 762 : 0.08441829 

boosting 762 : -0.5506876 
boosting mean 762 : -0.4585772 
boosting RMSE 762 : 0.1546393 

forest 762 : -0.4261037 
forest mean 762 : -0.4185350 
forest RMSE 762 : 0.05934811 

nnet 762 : -0.79066 
nnet mean 762 : -0.4004029 
nnet RMSE 762 : 0.1491383 


s: 763 
logit 763 : -0.5532756 
logit mean 763 : -0.4681364 
logit RMSE 763 : 0.08454524 

boosting 763 : -0.669353 
boosting mean 763 : -0.4588534 
boosting RMSE 763 : 0.1548452 

forest 763 : -0.4443153 
forest mean 763 : -0.4185688 
forest RMSE 763 : 0.0593309 

nnet 763 : -0.3760705 
nnet mean 763 : -0.400371 
nnet RMSE 763 : 0.1490430 


s: 764 
logit 764 : -0.4054525 
logit mean 764 : -0.4680543 
logit RMSE 764 : 0.08449012 

boosting 764 : -0.3498274 
boosting mean 764 : -0.4587107 
boosting RMSE 764 : 0.1547545 

forest 764 : -0.3118278 
forest mean 764 : -0.4184291 
forest RMSE 764 : 0.05937781 

nnet 764 : -0.5711643 
nnet mean 764 : -0.4005945 
nnet RMSE 764 : 0.1490741 


s: 765 
logit 765 : -0.4485656 
logit mean 765 : -0.4680289 
logit RMSE 765 : 0.08445314 

boosting 765 : -0.5018751 
boosting mean 765 : -0.4587671 
boosting RMSE 765 : 0.1546972 

forest 765 : -0.429797 
forest mean 765 : -0.418444 
forest RMSE 765 : 0.05934876 

nnet 765 : -0.5878787 
nnet mean 765 : -0.4008394 
nnet RMSE 765 : 0.1491314 


s: 766 
logit 766 : -0.4113236 
logit mean 766 : -0.4679548 
logit RMSE 766 : 0.08439899 

boosting 766 : -0.3588685 
boosting mean 766 : -0.4586367 
boosting RMSE 766 : 0.1546033 

forest 766 : -0.2799648 
forest mean 766 : -0.4182632 
forest RMSE 766 : 0.05946837 

nnet 766 : -0.6476239 
nnet mean 766 : -0.4011615 
nnet RMSE 766 : 0.1493024 


s: 767 
logit 767 : -0.4146811 
logit mean 767 : -0.4678854 
logit RMSE 767 : 0.08434562 

boosting 767 : -0.4556563 
boosting mean 767 : -0.4586328 
boosting RMSE 767 : 0.1545156 

forest 767 : -0.3894566 
forest mean 767 : -0.4182256 
forest RMSE 767 : 0.05943081 

nnet 767 : -0.4386625 
nnet mean 767 : -0.4012104 
nnet RMSE 767 : 0.1492116 


s: 768 
logit 768 : -0.5234793 
logit mean 768 : -0.4679578 
logit RMSE 768 : 0.08440837 

boosting 768 : -0.4741612 
boosting mean 768 : -0.4586531 
boosting RMSE 768 : 0.1544381 

forest 768 : -0.5448541 
forest mean 768 : -0.4183905 
forest RMSE 768 : 0.05962167 

nnet 768 : -0.553937 
nnet mean 768 : -0.4014093 
nnet RMSE 768 : 0.1492178 


s: 769 
logit 769 : -0.4778139 
logit mean 769 : -0.4679706 
logit RMSE 769 : 0.08440013 

boosting 769 : -0.8224092 
boosting mean 769 : -0.4591261 
boosting RMSE 769 : 0.1550875 

forest 769 : -0.4156886 
forest mean 769 : -0.418387 
forest RMSE 769 : 0.05958558 

nnet 769 : -0.5241861 
nnet mean 769 : -0.4015689 
nnet RMSE 769 : 0.1491880 


s: 770 
logit 770 : -0.5719322 
logit mean 770 : -0.4681056 
logit RMSE 770 : 0.08457258 

boosting 770 : -0.5263971 
boosting mean 770 : -0.4592134 
boosting RMSE 770 : 0.1550537 

forest 770 : -0.5131053 
forest mean 770 : -0.41851 
forest RMSE 770 : 0.05968622 

nnet 770 : -0.4271358 
nnet mean 770 : -0.4016021 
nnet RMSE 770 : 0.1490943 


s: 771 
logit 771 : -0.4600681 
logit mean 771 : -0.4680952 
logit RMSE 771 : 0.0845454 

boosting 771 : -0.4005572 
boosting mean 771 : -0.4591374 
boosting RMSE 771 : 0.1549531 

forest 771 : -0.4357416 
forest mean 771 : -0.4185324 
forest RMSE 771 : 0.05966138 

nnet 771 : -0.4593721 
nnet mean 771 : -0.4016771 
nnet RMSE 771 : 0.1490129 


s: 772 
logit 772 : -0.4280814 
logit mean 772 : -0.4680434 
logit RMSE 772 : 0.08449667 

boosting 772 : -0.6716757 
boosting mean 772 : -0.4594127 
boosting RMSE 772 : 0.1551611 

forest 772 : -0.4135694 
forest mean 772 : -0.4185259 
forest RMSE 772 : 0.05962473 

nnet 772 : -0.6724369 
nnet mean 772 : -0.4020278 
nnet RMSE 772 : 0.1492388 


s: 773 
logit 773 : -0.5446229 
logit mean 773 : -0.4681424 
logit RMSE 773 : 0.08460206 

boosting 773 : -0.6081004 
boosting mean 773 : -0.459605 
boosting RMSE 773 : 0.1552413 

forest 773 : -0.5504702 
forest mean 773 : -0.4186966 
forest RMSE 773 : 0.05983143 

nnet 773 : -0.3056439 
nnet mean 773 : -0.4019031 
nnet RMSE 773 : 0.1491809 


s: 774 
logit 774 : -0.4816714 
logit mean 774 : -0.4681599 
logit RMSE 774 : 0.08459834 

boosting 774 : -0.4191738 
boosting mean 774 : -0.4595528 
boosting RMSE 774 : 0.1551425 

forest 774 : -0.4167205 
forest mean 774 : -0.4186941 
forest RMSE 774 : 0.05979578 

nnet 774 : -0.3533457 
nnet mean 774 : -0.4018404 
nnet RMSE 774 : 0.1490939 


s: 775 
logit 775 : -0.435395 
logit mean 775 : -0.4681176 
logit RMSE 775 : 0.0845533 

boosting 775 : -0.6010605 
boosting mean 775 : -0.4597354 
boosting RMSE 775 : 0.1552105 

forest 775 : -0.4173038 
forest mean 775 : -0.4186923 
forest RMSE 775 : 0.05976043 

nnet 775 : -0.2821503 
nnet mean 775 : -0.4016859 
nnet RMSE 775 : 0.1490578 


s: 776 
logit 776 : -0.3971411 
logit mean 776 : -0.4680262 
logit RMSE 776 : 0.08449886 

boosting 776 : -0.3756539 
boosting mean 776 : -0.459627 
boosting RMSE 776 : 0.1551129 

forest 776 : -0.4430783 
forest mean 776 : -0.4187237 
forest RMSE 776 : 0.05974193 

nnet 776 : -0.5167431 
nnet mean 776 : -0.4018342 
nnet RMSE 776 : 0.1490207 


s: 777 
logit 777 : -0.4996227 
logit mean 777 : -0.4680668 
logit RMSE 777 : 0.08452007 

boosting 777 : -0.3795438 
boosting mean 777 : -0.459524 
boosting RMSE 777 : 0.1550148 

forest 777 : -0.3948052 
forest mean 777 : -0.4186929 
forest RMSE 777 : 0.05970376 

nnet 777 : -0.2462518 
nnet mean 777 : -0.401634 
nnet RMSE 777 : 0.1490268 


s: 778 
logit 778 : -0.4879808 
logit mean 778 : -0.4680924 
logit RMSE 778 : 0.0845246 

boosting 778 : -0.5123061 
boosting mean 778 : -0.4595918 
boosting RMSE 778 : 0.1549675 

forest 778 : -0.4446786 
forest mean 778 : -0.4187263 
forest RMSE 778 : 0.05968688 

nnet 778 : -0.4261657 
nnet mean 778 : -0.4016655 
nnet RMSE 778 : 0.148934 


s: 779 
logit 779 : -0.4992616 
logit mean 779 : -0.4681324 
logit RMSE 779 : 0.08454517 

boosting 779 : -0.5660775 
boosting mean 779 : -0.4597285 
boosting RMSE 779 : 0.1549823 

forest 779 : -0.4620497 
forest mean 779 : -0.4187819 
forest RMSE 779 : 0.05968997 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 779 : -0.2182036 
nnet mean 779 : -0.40143 
nnet RMSE 779 : 0.1489808 


s: 780 
logit 780 : -0.4642463 
logit mean 780 : -0.4681274 
logit RMSE 780 : 0.08452227 

boosting 780 : -0.4723734 
boosting mean 780 : -0.4597447 
boosting RMSE 780 : 0.1549046 

forest 780 : -0.3760472 
forest mean 780 : -0.4187272 
forest RMSE 780 : 0.05965786 

nnet 780 : -0.5156784 
nnet mean 780 : -0.4015765 
nnet RMSE 780 : 0.1489429 


s: 781 
logit 781 : -0.4291539 
logit mean 781 : -0.4680775 
logit RMSE 781 : 0.08447458 

boosting 781 : -0.1411962 
boosting mean 781 : -0.4593368 
boosting RMSE 781 : 0.1550821 

forest 781 : -0.4844984 
forest mean 781 : -0.4188114 
forest RMSE 781 : 0.05969627 

nnet 781 : -0.2921938 
nnet mean 781 : -0.4014364 
nnet RMSE 781 : 0.1488975 


s: 782 
logit 782 : -0.4865596 
logit mean 782 : -0.4681012 
logit RMSE 782 : 0.08447728 

boosting 782 : -0.506996 
boosting mean 782 : -0.4593978 
boosting RMSE 782 : 0.1550301 

forest 782 : -0.3779525 
forest mean 782 : -0.4187591 
forest RMSE 782 : 0.0596633 

nnet 782 : -0.5405204 
nnet mean 782 : -0.4016143 
nnet RMSE 782 : 0.1488871 


s: 783 
logit 783 : -0.4931487 
logit mean 783 : -0.4681332 
logit RMSE 783 : 0.08448892 

boosting 783 : -0.3995737 
boosting mean 783 : -0.4593214 
boosting RMSE 783 : 0.1549311 

forest 783 : -0.5027669 
forest mean 783 : -0.4188664 
forest RMSE 783 : 0.05973819 

nnet 783 : -0.4921309 
nnet mean 783 : -0.4017299 
nnet RMSE 783 : 0.1488284 


s: 784 
logit 784 : -0.5120958 
logit mean 784 : -0.4681892 
logit RMSE 784 : 0.08452988 

boosting 784 : -0.5263294 
boosting mean 784 : -0.4594068 
boosting RMSE 784 : 0.154898 

forest 784 : -0.3986602 
forest mean 784 : -0.4188406 
forest RMSE 784 : 0.0597001 

nnet 784 : -0.2688992 
nnet mean 784 : -0.4015604 
nnet RMSE 784 : 0.1488071 


s: 785 
logit 785 : -0.455422 
logit mean 785 : -0.468173 
logit RMSE 785 : 0.08449918 

boosting 785 : -0.3164666 
boosting mean 785 : -0.4592248 
boosting RMSE 785 : 0.154828 

forest 785 : -0.4594002 
forest mean 785 : -0.4188923 
forest RMSE 785 : 0.05969972 

nnet 785 : -0.3854795 
nnet mean 785 : -0.40154 
nnet RMSE 785 : 0.1487132 


s: 786 
logit 786 : -0.5167282 
logit mean 786 : -0.4682348 
logit RMSE 786 : 0.08454799 

boosting 786 : -0.4891048 
boosting mean 786 : -0.4592628 
boosting RMSE 786 : 0.1547621 

forest 786 : -0.4022423 
forest mean 786 : -0.4188711 
forest RMSE 786 : 0.05966178 

nnet 786 : -0.2797571 
nnet mean 786 : -0.401385 
nnet RMSE 786 : 0.1486805 


s: 787 
logit 787 : -0.4866898 
logit mean 787 : -0.4682582 
logit RMSE 787 : 0.08455074 

boosting 787 : -0.5469025 
boosting mean 787 : -0.4593741 
boosting RMSE 787 : 0.1547524 

forest 787 : -0.4187074 
forest mean 787 : -0.4188709 
forest RMSE 787 : 0.0596276 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 787 : -0.2480931 
nnet mean 787 : -0.4011902 
nnet RMSE 787 : 0.1486846 


s: 788 
logit 788 : -0.4055789 
logit mean 788 : -0.4681787 
logit RMSE 788 : 0.08449731 

boosting 788 : -0.5694371 
boosting mean 788 : -0.4595138 
boosting RMSE 788 : 0.1547719 

forest 788 : -0.4560243 
forest mean 788 : -0.4189181 
forest RMSE 788 : 0.05962316 

nnet 788 : -0.446102 
nnet mean 788 : -0.4012472 
nnet RMSE 788 : 0.1485993 


s: 789 
logit 789 : -0.4676252 
logit mean 789 : -0.468178 
logit RMSE 789 : 0.08447806 

boosting 789 : -0.5532981 
boosting mean 789 : -0.4596327 
boosting RMSE 789 : 0.1547700 

forest 789 : -0.4304636 
forest mean 789 : -0.4189327 
forest RMSE 789 : 0.05959523 

nnet 789 : -0.3837962 
nnet mean 789 : -0.4012251 
nnet RMSE 789 : 0.1485062 


s: 790 
logit 790 : -0.4576538 
logit mean 790 : -0.4681646 
logit RMSE 790 : 0.08444949 

boosting 790 : -0.5427285 
boosting mean 790 : -0.4597379 
boosting RMSE 790 : 0.1547554 

forest 790 : -0.4205677 
forest mean 790 : -0.4189348 
forest RMSE 790 : 0.059562 

nnet 790 : -0.2575209 
nnet mean 790 : -0.4010432 
nnet RMSE 790 : 0.1484988 


s: 791 
logit 791 : -0.4532687 
logit mean 791 : -0.4681458 
logit RMSE 791 : 0.08441734 

boosting 791 : -0.2858583 
boosting mean 791 : -0.459518 
boosting RMSE 791 : 0.1547108 

forest 791 : -0.3568242 
forest mean 791 : -0.4188562 
forest RMSE 791 : 0.05954413 

nnet 791 : -0.5183981 
nnet mean 791 : -0.4011916 
nnet RMSE 791 : 0.1484646 


s: 792 
logit 792 : -0.4552448 
logit mean 792 : -0.4681295 
logit RMSE 792 : 0.08438687 

boosting 792 : -0.4330569 
boosting mean 792 : -0.4594846 
boosting RMSE 792 : 0.1546175 

forest 792 : -0.3553480 
forest mean 792 : -0.4187761 
forest RMSE 792 : 0.05952768 

nnet 792 : -0.1352075 
nnet mean 792 : -0.4008557 
nnet RMSE 792 : 0.1486688 


s: 793 
logit 793 : -0.5986657 
logit mean 793 : -0.4682941 
logit RMSE 793 : 0.0846282 

boosting 793 : -0.6065486 
boosting mean 793 : -0.4596701 
boosting RMSE 793 : 0.154694 

forest 793 : -0.4840328 
forest mean 793 : -0.4188583 
forest RMSE 793 : 0.05956493 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 793 : -0.2154888 
nnet mean 793 : -0.400622 
nnet RMSE 793 : 0.1487195 


s: 794 
logit 794 : -0.4317599 
logit mean 794 : -0.4682481 
logit RMSE 794 : 0.08458241 

boosting 794 : -0.5715135 
boosting mean 794 : -0.4598109 
boosting RMSE 794 : 0.1547163 

forest 794 : -0.3765216 
forest mean 794 : -0.418805 
forest RMSE 794 : 0.05953324 

nnet 794 : -0.4097987 
nnet mean 794 : -0.4006335 
nnet RMSE 794 : 0.1486262 


s: 795 
logit 795 : -0.4358827 
logit mean 795 : -0.4682074 
logit RMSE 795 : 0.08453878 

boosting 795 : -0.2257056 
boosting mean 795 : -0.4595165 
boosting RMSE 795 : 0.1547425 

forest 795 : -0.2483332 
forest mean 795 : -0.4185906 
forest RMSE 795 : 0.05973845 

nnet 795 : -0.4065013 
nnet mean 795 : -0.4006409 
nnet RMSE 795 : 0.1485329 


s: 796 
logit 796 : -0.4831078 
logit mean 796 : -0.4682261 
logit RMSE 796 : 0.084537 

boosting 796 : -0.2554832 
boosting mean 796 : -0.4592601 
boosting RMSE 796 : 0.1547301 

forest 796 : -0.3396142 
forest mean 796 : -0.4184914 
forest RMSE 796 : 0.05973927 

nnet 796 : -0.2853237 
nnet mean 796 : -0.4004961 
nnet RMSE 796 : 0.1484952 


s: 797 
logit 797 : -0.4905983 
logit mean 797 : -0.4682542 
logit RMSE 797 : 0.08454487 

boosting 797 : -0.5481453 
boosting mean 797 : -0.4593717 
boosting RMSE 797 : 0.154722 

forest 797 : -0.3715213 
forest mean 797 : -0.4184324 
forest RMSE 797 : 0.0597103 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 797 : -0.3096735 
nnet mean 797 : -0.4003821 
nnet RMSE 797 : 0.1484365 


s: 798 
logit 798 : -0.4085928 
logit mean 798 : -0.4681794 
logit RMSE 798 : 0.08449243 

boosting 798 : -0.4439852 
boosting mean 798 : -0.4593524 
boosting RMSE 798 : 0.1546329 

forest 798 : -0.3703321 
forest mean 798 : -0.4183722 
forest RMSE 798 : 0.05968212 

nnet 798 : -0.3037358 
nnet mean 798 : -0.400261 
nnet RMSE 798 : 0.1483826 


s: 799 
logit 799 : -0.4217345 
logit mean 799 : -0.4681213 
logit RMSE 799 : 0.08444304 

boosting 799 : -0.4281512 
boosting mean 799 : -0.4593133 
boosting RMSE 799 : 0.1545393 

forest 799 : -0.3232992 
forest mean 799 : -0.4182532 
forest RMSE 799 : 0.05970645 

nnet 799 : -0.4620634 
nnet mean 799 : -0.4003383 
nnet RMSE 799 : 0.1483060 


s: 800 
logit 800 : -0.3818421 
logit mean 800 : -0.4680135 
logit RMSE 800 : 0.08439269 

boosting 800 : -0.6779507 
boosting mean 800 : -0.4595866 
boosting RMSE 800 : 0.154755 

forest 800 : -0.437504 
forest mean 800 : -0.4182772 
forest RMSE 800 : 0.05968385 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 800 : -0.2242434 
nnet mean 800 : -0.4001182 
nnet RMSE 800 : 0.1483434 


s: 801 
logit 801 : -0.4788848 
logit mean 801 : -0.468027 
logit RMSE 801 : 0.08438603 

boosting 801 : -0.3070398 
boosting mean 801 : -0.4593962 
boosting RMSE 801 : 0.1546932 

forest 801 : -0.3203538 
forest mean 801 : -0.418155 
forest RMSE 801 : 0.05971293 

nnet 801 : -0.6875284 
nnet mean 801 : -0.400477 
nnet RMSE 801 : 0.1485985 


s: 802 
logit 802 : -0.434749 
logit mean 802 : -0.4679855 
logit RMSE 802 : 0.08434233 

boosting 802 : -0.3662062 
boosting mean 802 : -0.45928 
boosting RMSE 802 : 0.1546014 

forest 802 : -0.4731545 
forest mean 802 : -0.4182236 
forest RMSE 802 : 0.05973158 

nnet 802 : -0.6929553 
nnet mean 802 : -0.4008417 
nnet RMSE 802 : 0.1488657 


s: 803 
logit 803 : -0.4911681 
logit mean 803 : -0.4680144 
logit RMSE 803 : 0.08435118 

boosting 803 : -0.6119982 
boosting mean 803 : -0.4594702 
boosting RMSE 803 : 0.1546861 

forest 803 : -0.4410291 
forest mean 803 : -0.418252 
forest RMSE 803 : 0.05971193 

nnet 803 : -0.2548931 
nnet mean 803 : -0.40066 
nnet RMSE 803 : 0.1488611 


s: 804 
logit 804 : -0.6098978 
logit mean 804 : -0.4681909 
logit RMSE 804 : 0.0846231 

boosting 804 : -0.3538035 
boosting mean 804 : -0.4593387 
boosting RMSE 804 : 0.1545985 

forest 804 : -0.4288696 
forest mean 804 : -0.4182652 
forest RMSE 804 : 0.05968347 

nnet 804 : -0.4141078 
nnet mean 804 : -0.4006767 
nnet RMSE 804 : 0.1487693 


s: 805 
logit 805 : -0.4373728 
logit mean 805 : -0.4681526 
logit RMSE 805 : 0.08458078 

boosting 805 : -0.7075025 
boosting mean 805 : -0.459647 
boosting RMSE 805 : 0.1548821 

forest 805 : -0.4280394 
forest mean 805 : -0.4182773 
forest RMSE 805 : 0.05965457 

nnet 805 : -0.6423122 
nnet mean 805 : -0.4009769 
nnet RMSE 805 : 0.1489219 


s: 806 
logit 806 : -0.4488349 
logit mean 806 : -0.4681286 
logit RMSE 806 : 0.0845458 

boosting 806 : -0.5435881 
boosting mean 806 : -0.4597512 
boosting RMSE 806 : 0.1548686 

forest 806 : -0.3980765 
forest mean 806 : -0.4182523 
forest RMSE 806 : 0.05961759 

nnet 806 : -0.3342895 
nnet mean 806 : -0.4008941 
nnet RMSE 806 : 0.1488475 


s: 807 
logit 807 : -0.4486760 
logit mean 807 : -0.4681045 
logit RMSE 807 : 0.08451077 

boosting 807 : -0.455233 
boosting mean 807 : -0.4597456 
boosting RMSE 807 : 0.1547848 

forest 807 : -0.4786379 
forest mean 807 : -0.4183271 
forest RMSE 807 : 0.05964492 

nnet 807 : -0.5680953 
nnet mean 807 : -0.4011013 
nnet RMSE 807 : 0.1488729 


s: 808 
logit 808 : -0.492803 
logit mean 808 : -0.4681351 
logit RMSE 808 : 0.08452153 

boosting 808 : -0.4837409 
boosting mean 808 : -0.4597753 
boosting RMSE 808 : 0.1547170 

forest 808 : -0.4656809 
forest mean 808 : -0.4183857 
forest RMSE 808 : 0.05965276 

nnet 808 : -0.3933027 
nnet mean 808 : -0.4010917 
nnet RMSE 808 : 0.1487810 


s: 809 
logit 809 : -0.5192814 
logit mean 809 : -0.4681983 
logit RMSE 809 : 0.08457332 

boosting 809 : -0.4382084 
boosting mean 809 : -0.4597486 
boosting RMSE 809 : 0.1546272 

forest 809 : -0.4110419 
forest mean 809 : -0.4183766 
forest RMSE 809 : 0.05961715 

nnet 809 : -0.2425310 
nnet mean 809 : -0.4008957 
nnet RMSE 809 : 0.148792 


s: 810 
logit 810 : -0.5009315 
logit mean 810 : -0.4682387 
logit RMSE 810 : 0.08459546 

boosting 810 : -0.2471898 
boosting mean 810 : -0.4594862 
boosting RMSE 810 : 0.154625 

forest 810 : -0.5406557 
forest mean 810 : -0.4185276 
forest RMSE 810 : 0.05978496 

nnet 810 : -0.4041411 
nnet mean 810 : -0.4008997 
nnet RMSE 810 : 0.1487002 


s: 811 
logit 811 : -0.5418432 
logit mean 811 : -0.4683295 
logit RMSE 811 : 0.08468989 

boosting 811 : -0.8133436 
boosting mean 811 : -0.4599225 
boosting RMSE 811 : 0.1552098 

forest 811 : -0.3322699 
forest mean 811 : -0.4184212 
forest RMSE 811 : 0.0597954 

nnet 811 : -0.504281 
nnet mean 811 : -0.4010271 
nnet RMSE 811 : 0.1486536 


s: 812 
logit 812 : -0.4233135 
logit mean 812 : -0.468274 
logit RMSE 812 : 0.08464167 

boosting 812 : -0.3990711 
boosting mean 812 : -0.4598476 
boosting RMSE 812 : 0.1551142 

forest 812 : -0.3913012 
forest mean 812 : -0.4183878 
forest RMSE 812 : 0.05975935 

nnet 812 : -0.5686395 
nnet mean 812 : -0.4012336 
nnet RMSE 812 : 0.1486799 


s: 813 
logit 813 : -0.4369343 
logit mean 813 : -0.4682355 
logit RMSE 813 : 0.08459952 

boosting 813 : -0.7161788 
boosting mean 813 : -0.4601629 
boosting RMSE 813 : 0.1554149 

forest 813 : -0.3931476 
forest mean 813 : -0.4183568 
forest RMSE 813 : 0.05972307 

nnet 813 : -0.4232188 
nnet mean 813 : -0.4012606 
nnet RMSE 813 : 0.1485906 


s: 814 
logit 814 : -0.5491178 
logit mean 814 : -0.4683349 
logit RMSE 814 : 0.08470893 

boosting 814 : -0.5902714 
boosting mean 814 : -0.4603227 
boosting RMSE 814 : 0.1554625 

forest 814 : -0.3674042 
forest mean 814 : -0.4182942 
forest RMSE 814 : 0.05969731 

nnet 814 : -0.4384961 
nnet mean 814 : -0.4013063 
nnet RMSE 814 : 0.1485055 


s: 815 
logit 815 : -0.420136 
logit mean 815 : -0.4682757 
logit RMSE 815 : 0.08465989 

boosting 815 : -0.3246114 
boosting mean 815 : -0.4601562 
boosting RMSE 815 : 0.1553895 

forest 815 : -0.4659733 
forest mean 815 : -0.4183527 
forest RMSE 815 : 0.05970542 

nnet 815 : -0.5279898 
nnet mean 815 : -0.4014618 
nnet RMSE 815 : 0.1484820 


s: 816 
logit 816 : -0.5359165 
logit mean 816 : -0.4683586 
logit RMSE 816 : 0.08474168 

boosting 816 : -0.5031662 
boosting mean 816 : -0.4602089 
boosting RMSE 816 : 0.1553363 

forest 816 : -0.491189 
forest mean 816 : -0.4184419 
forest RMSE 816 : 0.05975415 

nnet 816 : -0.3948591 
nnet mean 816 : -0.4014537 
nnet RMSE 816 : 0.1483911 


s: 817 
logit 817 : -0.4651658 
logit mean 817 : -0.4683547 
logit RMSE 817 : 0.08472048 

boosting 817 : -0.4593078 
boosting mean 817 : -0.4602078 
boosting RMSE 817 : 0.1552550 

forest 817 : -0.5249154 
forest mean 817 : -0.4185723 
forest RMSE 817 : 0.05987727 

nnet 817 : -0.6781035 
nnet mean 817 : -0.4017923 
nnet RMSE 817 : 0.1486191 


s: 818 
logit 818 : -0.4542953 
logit mean 818 : -0.4683375 
logit RMSE 818 : 0.08468996 

boosting 818 : -0.6890686 
boosting mean 818 : -0.4604876 
boosting RMSE 818 : 0.1554889 

forest 818 : -0.4205936 
forest mean 818 : -0.4185747 
forest RMSE 818 : 0.05984499 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 818 : -0.2895241 
nnet mean 818 : -0.4016551 
nnet RMSE 818 : 0.1485785 


s: 819 
logit 819 : -0.4272336 
logit mean 819 : -0.4682873 
logit RMSE 819 : 0.0846436 

boosting 819 : -0.5770034 
boosting mean 819 : -0.4606298 
boosting RMSE 819 : 0.1555170 

forest 819 : -0.3988882 
forest mean 819 : -0.4185507 
forest RMSE 819 : 0.05980845 

nnet 819 : -0.4152692 
nnet mean 819 : -0.4016717 
nnet RMSE 819 : 0.1484887 


s: 820 
logit 820 : -0.5152746 
logit mean 820 : -0.4683446 
logit RMSE 820 : 0.0846877 

boosting 820 : -0.5059124 
boosting mean 820 : -0.4606851 
boosting RMSE 820 : 0.1554662 

forest 820 : -0.4268127 
forest mean 820 : -0.4185608 
forest RMSE 820 : 0.05977931 

nnet 820 : -0.5673838 
nnet mean 820 : -0.4018738 
nnet RMSE 820 : 0.1485132 


s: 821 
logit 821 : -0.5221982 
logit mean 821 : -0.4684102 
logit RMSE 821 : 0.08474348 

boosting 821 : -0.4456559 
boosting mean 821 : -0.4606668 
boosting RMSE 821 : 0.1553796 

forest 821 : -0.337685 
forest mean 821 : -0.4184623 
forest RMSE 821 : 0.05978246 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 821 : -0.2920301 
nnet mean 821 : -0.40174 
nnet RMSE 821 : 0.1484705 


s: 822 
logit 822 : -0.485592 
logit mean 822 : -0.4684311 
logit RMSE 822 : 0.08474452 

boosting 822 : -0.5347971 
boosting mean 822 : -0.4607569 
boosting RMSE 822 : 0.1553562 

forest 822 : -0.4444834 
forest mean 822 : -0.4184939 
forest RMSE 822 : 0.05976623 

nnet 822 : -0.4611038 
nnet mean 822 : -0.4018122 
nnet RMSE 822 : 0.1483955 


s: 823 
logit 823 : -0.427231 
logit mean 823 : -0.4683811 
logit RMSE 823 : 0.08469834 

boosting 823 : -0.7694026 
boosting mean 823 : -0.461132 
boosting RMSE 823 : 0.1557949 

forest 823 : -0.4103784 
forest mean 823 : -0.4184841 
forest RMSE 823 : 0.059731 

nnet 823 : -0.5966571 
nnet mean 823 : -0.4020489 
nnet RMSE 823 : 0.1484637 


s: 824 
logit 824 : -0.474122 
logit mean 824 : -0.468388 
logit RMSE 824 : 0.0846863 

boosting 824 : -0.4348729 
boosting mean 824 : -0.4611001 
boosting RMSE 824 : 0.1557050 

forest 824 : -0.3427331 
forest mean 824 : -0.4183921 
forest RMSE 824 : 0.05972808 

nnet 824 : -0.4792567 
nnet mean 824 : -0.4021426 
nnet RMSE 824 : 0.1483992 


s: 825 
logit 825 : -0.4437956 
logit mean 825 : -0.4683582 
logit RMSE 825 : 0.0846487 

boosting 825 : -0.3738342 
boosting mean 825 : -0.4609943 
boosting RMSE 825 : 0.1556133 

forest 825 : -0.5083789 
forest mean 825 : -0.4185012 
forest RMSE 825 : 0.059811 

nnet 825 : -0.4136056 
nnet mean 825 : -0.4021565 
nnet RMSE 825 : 0.1483100 


s: 826 
logit 826 : -0.5180624 
logit mean 826 : -0.4684184 
logit RMSE 826 : 0.08469712 

boosting 826 : -0.5643427 
boosting mean 826 : -0.4611194 
boosting RMSE 826 : 0.1556242 

forest 826 : -0.4584685 
forest mean 826 : -0.4185496 
forest RMSE 826 : 0.0598094 

nnet 826 : -0.5930836 
nnet mean 826 : -0.4023877 
nnet RMSE 826 : 0.1483724 


s: 827 
logit 827 : -0.4734303 
logit mean 827 : -0.4684245 
logit RMSE 827 : 0.0846844 

boosting 827 : -0.5665543 
boosting mean 827 : -0.4612469 
boosting RMSE 827 : 0.1556379 

forest 827 : -0.3888923 
forest mean 827 : -0.4185137 
forest RMSE 827 : 0.05977448 

nnet 827 : -0.2183265 
nnet mean 827 : -0.4021651 
nnet RMSE 827 : 0.1484172 


s: 828 
logit 828 : -0.4733793 
logit mean 828 : -0.4684304 
logit RMSE 828 : 0.08467166 

boosting 828 : -0.2608497 
boosting mean 828 : -0.4610049 
boosting RMSE 828 : 0.155619 

forest 828 : -0.319246 
forest mean 828 : -0.4183938 
forest RMSE 828 : 0.05980425 

nnet 828 : -0.3883649 
nnet mean 828 : -0.4021485 
nnet RMSE 828 : 0.1483281 


s: 829 
logit 829 : -0.4580094 
logit mean 829 : -0.4684179 
logit RMSE 829 : 0.08464456 

boosting 829 : -0.2342732 
boosting mean 829 : -0.4607314 
boosting RMSE 829 : 0.1556316 

forest 829 : -0.2965599 
forest mean 829 : -0.4182469 
forest RMSE 829 : 0.05987605 

nnet 829 : -0.3207852 
nnet mean 829 : -0.4020503 
nnet RMSE 829 : 0.1482641 


s: 830 
logit 830 : -0.4987303 
logit mean 830 : -0.4684544 
logit RMSE 830 : 0.08466294 

boosting 830 : -0.5462487 
boosting mean 830 : -0.4608344 
boosting RMSE 830 : 0.1556206 

forest 830 : -0.4286754 
forest mean 830 : -0.4182594 
forest RMSE 830 : 0.05984825 

nnet 830 : -0.1491733 
nnet mean 830 : -0.4017456 
nnet RMSE 830 : 0.1484303 


s: 831 
logit 831 : -0.4647383 
logit mean 831 : -0.4684499 
logit RMSE 831 : 0.08464178 

boosting 831 : -0.7837396 
boosting mean 831 : -0.461223 
boosting RMSE 831 : 0.1560956 

forest 831 : -0.479875 
forest mean 831 : -0.4183336 
forest RMSE 831 : 0.05987637 

nnet 831 : -0.4071556 
nnet mean 831 : -0.4017521 
nnet RMSE 831 : 0.1483412 


s: 832 
logit 832 : -0.4837636 
logit mean 832 : -0.4684683 
logit RMSE 832 : 0.08464073 

boosting 832 : -0.6824296 
boosting mean 832 : -0.4614889 
boosting RMSE 832 : 0.1563088 

forest 832 : -0.4788587 
forest mean 832 : -0.4184063 
forest RMSE 832 : 0.0599028 

nnet 832 : -0.6283486 
nnet mean 832 : -0.4020245 
nnet RMSE 832 : 0.1484633 


s: 833 
logit 833 : -0.4625088 
logit mean 833 : -0.4684612 
logit RMSE 833 : 0.08461763 

boosting 833 : -0.7316613 
boosting mean 833 : -0.4618132 
boosting RMSE 833 : 0.156637 

forest 833 : -0.4917508 
forest mean 833 : -0.4184944 
forest RMSE 833 : 0.05995117 

nnet 833 : -0.2765316 
nnet mean 833 : -0.4018738 
nnet RMSE 833 : 0.1484358 


s: 834 
logit 834 : -0.5196074 
logit mean 834 : -0.4685225 
logit RMSE 834 : 0.08466824 

boosting 834 : -0.516055 
boosting mean 834 : -0.4618783 
boosting RMSE 834 : 0.1565946 

forest 834 : -0.4083626 
forest mean 834 : -0.4184822 
forest RMSE 834 : 0.05991592 

nnet 834 : -0.1468771 
nnet mean 834 : -0.4015681 
nnet RMSE 834 : 0.1486055 


s: 835 
logit 835 : -0.3601196 
logit mean 835 : -0.4683927 
logit RMSE 835 : 0.08462878 

boosting 835 : -0.2030317 
boosting mean 835 : -0.4615683 
boosting RMSE 835 : 0.1566492 

forest 835 : -0.2480973 
forest mean 835 : -0.4182782 
forest RMSE 835 : 0.06011033 

nnet 835 : -0.2476352 
nnet mean 835 : -0.4013837 
nnet RMSE 835 : 0.1486100 


s: 836 
logit 836 : -0.4516417 
logit mean 836 : -0.4683726 
logit RMSE 836 : 0.084597 

boosting 836 : -0.3082989 
boosting mean 836 : -0.4613849 
boosting RMSE 836 : 0.1565876 

forest 836 : -0.3823520 
forest mean 836 : -0.4182352 
forest RMSE 836 : 0.06007747 

nnet 836 : -0.3663986 
nnet mean 836 : -0.4013419 
nnet RMSE 836 : 0.1485257 


s: 837 
logit 837 : -0.5405296 
logit mean 837 : -0.4684588 
logit RMSE 837 : 0.08468588 

boosting 837 : -0.7203566 
boosting mean 837 : -0.4616943 
boosting RMSE 837 : 0.1568853 

forest 837 : -0.4218198 
forest mean 837 : -0.4182395 
forest RMSE 837 : 0.06004631 

nnet 837 : -0.5396617 
nnet mean 837 : -0.4015072 
nnet RMSE 837 : 0.1485154 


s: 838 
logit 838 : -0.5533082 
logit mean 838 : -0.4685601 
logit RMSE 838 : 0.08480087 

boosting 838 : -0.3820225 
boosting mean 838 : -0.4615993 
boosting RMSE 838 : 0.1567929 

forest 838 : -0.4024632 
forest mean 838 : -0.4182207 
forest RMSE 838 : 0.06001053 

nnet 838 : -0.3778145 
nnet mean 838 : -0.4014789 
nnet RMSE 838 : 0.1484287 


s: 839 
logit 839 : -0.4226616 
logit mean 839 : -0.4685054 
logit RMSE 839 : 0.08475392 

boosting 839 : -0.4950445 
boosting mean 839 : -0.4616391 
boosting RMSE 839 : 0.1567338 

forest 839 : -0.3979863 
forest mean 839 : -0.4181965 
forest RMSE 839 : 0.0599748 

nnet 839 : -0.2740657 
nnet mean 839 : -0.401327 
nnet RMSE 839 : 0.1484039 


s: 840 
logit 840 : -0.487889 
logit mean 840 : -0.4685285 
logit RMSE 840 : 0.08475773 

boosting 840 : -0.4357008 
boosting mean 840 : -0.4616082 
boosting RMSE 840 : 0.1566453 

forest 840 : -0.4056599 
forest mean 840 : -0.4181816 
forest RMSE 840 : 0.05993941 

nnet 840 : -0.3996435 
nnet mean 840 : -0.401325 
nnet RMSE 840 : 0.1483156 


s: 841 
logit 841 : -0.4277961 
logit mean 841 : -0.46848 
logit RMSE 841 : 0.08471274 

boosting 841 : -0.7380108 
boosting mean 841 : -0.4619369 
boosting RMSE 841 : 0.1569854 

forest 841 : -0.4637309 
forest mean 841 : -0.4182358 
forest RMSE 841 : 0.05994406 

nnet 841 : -0.5675859 
nnet mean 841 : -0.4015227 
nnet RMSE 841 : 0.14834 


s: 842 
logit 842 : -0.3781186 
logit mean 842 : -0.4683727 
logit RMSE 842 : 0.08466578 

boosting 842 : -0.6900851 
boosting mean 842 : -0.4622079 
boosting RMSE 842 : 0.1572104 

forest 842 : -0.3407737 
forest mean 842 : -0.4181438 
forest RMSE 842 : 0.05994321 

nnet 842 : -0.4335254 
nnet mean 842 : -0.4015607 
nnet RMSE 842 : 0.1482564 


s: 843 
logit 843 : -0.5156565 
logit mean 843 : -0.4684288 
logit RMSE 843 : 0.08470926 

boosting 843 : -0.2119278 
boosting mean 843 : -0.461911 
boosting RMSE 843 : 0.1572506 

forest 843 : -0.3984593 
forest mean 843 : -0.4181204 
forest RMSE 843 : 0.05990767 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 843 : -0.1683852 
nnet mean 843 : -0.4012841 
nnet RMSE 843 : 0.148383 


s: 844 
logit 844 : -0.3937864 
logit mean 844 : -0.4683404 
logit RMSE 844 : 0.08465933 

boosting 844 : -0.323667 
boosting mean 844 : -0.4617472 
boosting RMSE 844 : 0.1571793 

forest 844 : -0.4061978 
forest mean 844 : -0.4181063 
forest RMSE 844 : 0.05987255 

nnet 844 : -0.3892434 
nnet mean 844 : -0.4012698 
nnet RMSE 844 : 0.1482955 


s: 845 
logit 845 : -0.3989741 
logit mean 845 : -0.4682583 
logit RMSE 845 : 0.08460923 

boosting 845 : -0.46502 
boosting mean 845 : -0.461751 
boosting RMSE 845 : 0.1571022 

forest 845 : -0.4867896 
forest mean 845 : -0.4181876 
forest RMSE 845 : 0.05991155 

nnet 845 : -0.6200941 
nnet mean 845 : -0.4015288 
nnet RMSE 845 : 0.1484010 


s: 846 
logit 846 : -0.4435102 
logit mean 846 : -0.468229 
logit RMSE 846 : 0.08457244 

boosting 846 : -0.6140889 
boosting mean 846 : -0.4619311 
boosting RMSE 846 : 0.1571818 

forest 846 : -0.5450375 
forest mean 846 : -0.4183375 
forest RMSE 846 : 0.06008341 

nnet 846 : -0.2491175 
nnet mean 846 : -0.4013487 
nnet RMSE 846 : 0.148404 


s: 847 
logit 847 : -0.4513867 
logit mean 847 : -0.4682091 
logit RMSE 847 : 0.08454094 

boosting 847 : -0.4983567 
boosting mean 847 : -0.4619741 
boosting RMSE 847 : 0.1571253 

forest 847 : -0.3726448 
forest mean 847 : -0.4182836 
forest RMSE 847 : 0.06005529 

nnet 847 : -0.2004987 
nnet mean 847 : -0.4011115 
nnet RMSE 847 : 0.1484747 


s: 848 
logit 848 : -0.4231363 
logit mean 848 : -0.468156 
logit RMSE 848 : 0.08449482 

boosting 848 : -0.2698863 
boosting mean 848 : -0.4617476 
boosting RMSE 848 : 0.1570962 

forest 848 : -0.3826512 
forest mean 848 : -0.4182416 
forest RMSE 848 : 0.06002282 

nnet 848 : -0.496637 
nnet mean 848 : -0.4012242 
nnet RMSE 848 : 0.1484242 


s: 849 
logit 849 : -0.4689329 
logit mean 849 : -0.4681569 
logit RMSE 849 : 0.08447817 

boosting 849 : -0.5253754 
boosting mean 849 : -0.4618225 
boosting RMSE 849 : 0.1570626 

forest 849 : -0.4939672 
forest mean 849 : -0.4183308 
forest RMSE 849 : 0.06007409 

nnet 849 : -0.2314920 
nnet mean 849 : -0.4010243 
nnet RMSE 849 : 0.1484495 


s: 850 
logit 850 : -0.4792482 
logit mean 850 : -0.4681699 
logit RMSE 850 : 0.08447221 

boosting 850 : -0.3155546 
boosting mean 850 : -0.4616505 
boosting RMSE 850 : 0.1569969 

forest 850 : -0.448217 
forest mean 850 : -0.4183659 
forest RMSE 850 : 0.06006152 

nnet 850 : -0.3028884 
nnet mean 850 : -0.4009088 
nnet RMSE 850 : 0.1483995 


s: 851 
logit 851 : -0.4397605 
logit mean 851 : -0.4681366 
logit RMSE 851 : 0.08443357 

boosting 851 : -0.2790407 
boosting mean 851 : -0.4614359 
boosting RMSE 851 : 0.1569594 

forest 851 : -0.3436598 
forest mean 851 : -0.4182781 
forest RMSE 851 : 0.06005728 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 851 : -0.2956700 
nnet mean 851 : -0.4007851 
nnet RMSE 851 : 0.1483554 


s: 852 
logit 852 : -0.4978691 
logit mean 852 : -0.4681715 
logit RMSE 852 : 0.08445059 

boosting 852 : -0.500556 
boosting mean 852 : -0.4614818 
boosting RMSE 852 : 0.1569051 

forest 852 : -0.5055452 
forest mean 852 : -0.4183806 
forest RMSE 852 : 0.06013084 

nnet 852 : -0.3627773 
nnet mean 852 : -0.4007405 
nnet RMSE 852 : 0.1482738 


s: 853 
logit 853 : -0.4612149 
logit mean 853 : -0.4681633 
logit RMSE 853 : 0.0844271 

boosting 853 : -0.3220275 
boosting mean 853 : -0.4613183 
boosting RMSE 853 : 0.1568358 

forest 853 : -0.5200592 
forest mean 853 : -0.4184998 
forest RMSE 853 : 0.06023602 

nnet 853 : -0.1698444 
nnet mean 853 : -0.4004698 
nnet RMSE 853 : 0.1483963 


s: 854 
logit 854 : -0.4821206 
logit mean 854 : -0.4681797 
logit RMSE 854 : 0.08442443 

boosting 854 : -0.4541989 
boosting mean 854 : -0.46131 
boosting RMSE 854 : 0.1567550 

forest 854 : -0.4656797 
forest mean 854 : -0.418555 
forest RMSE 854 : 0.06024268 

nnet 854 : -0.1976189 
nnet mean 854 : -0.4002323 
nnet RMSE 854 : 0.1484709 


s: 855 
logit 855 : -0.4747676 
logit mean 855 : -0.4681874 
logit RMSE 855 : 0.08441378 

boosting 855 : -0.8534801 
boosting mean 855 : -0.4617686 
boosting RMSE 855 : 0.157429 

forest 855 : -0.4403279 
forest mean 855 : -0.4185805 
forest RMSE 855 : 0.06022323 

nnet 855 : -0.1849913 
nnet mean 855 : -0.3999806 
nnet RMSE 855 : 0.1485662 


s: 856 
logit 856 : -0.5133845 
logit mean 856 : -0.4682402 
logit RMSE 856 : 0.08445342 

boosting 856 : -0.4356329 
boosting mean 856 : -0.4617381 
boosting RMSE 856 : 0.1573417 

forest 856 : -0.4601306 
forest mean 856 : -0.418629 
forest RMSE 856 : 0.06022312 

nnet 856 : -0.2319796 
nnet mean 856 : -0.3997843 
nnet RMSE 856 : 0.1485904 


s: 857 
logit 857 : -0.4216013 
logit mean 857 : -0.4681857 
logit RMSE 857 : 0.08440736 

boosting 857 : -0.8330589 
boosting mean 857 : -0.4621714 
boosting RMSE 857 : 0.1579442 

forest 857 : -0.3855385 
forest mean 857 : -0.4185904 
forest RMSE 857 : 0.06019 

nnet 857 : -0.5857025 
nnet mean 857 : -0.4000012 
nnet RMSE 857 : 0.1486391 


s: 858 
logit 858 : -0.4665485 
logit mean 858 : -0.4681838 
logit RMSE 858 : 0.08438875 

boosting 858 : -0.5271853 
boosting mean 858 : -0.4622472 
boosting RMSE 858 : 0.1579118 

forest 858 : -0.3368745 
forest mean 858 : -0.4184952 
forest RMSE 858 : 0.06019351 

nnet 858 : -0.274401 
nnet mean 858 : -0.3998549 
nnet RMSE 858 : 0.1486143 


s: 859 
logit 859 : -0.4150664 
logit mean 859 : -0.468122 
logit RMSE 859 : 0.08434118 

boosting 859 : -0.4581868 
boosting mean 859 : -0.4622424 
boosting RMSE 859 : 0.1578324 

forest 859 : -0.3714751 
forest mean 859 : -0.4184404 
forest RMSE 859 : 0.06016633 

nnet 859 : -0.4606048 
nnet mean 859 : -0.3999256 
nnet RMSE 859 : 0.1485422 


s: 860 
logit 860 : -0.4279323 
logit mean 860 : -0.4680753 
logit RMSE 860 : 0.08429751 

boosting 860 : -0.6067355 
boosting mean 860 : -0.4624105 
boosting RMSE 860 : 0.1578980 

forest 860 : -0.491663 
forest mean 860 : -0.4185256 
forest RMSE 860 : 0.06021253 

nnet 860 : -0.4969094 
nnet mean 860 : -0.4000383 
nnet RMSE 860 : 0.1484926 


s: 861 
logit 861 : -0.4128415 
logit mean 861 : -0.4680111 
logit RMSE 861 : 0.08424968 

boosting 861 : -0.5713098 
boosting mean 861 : -0.4625369 
boosting RMSE 861 : 0.1579143 

forest 861 : -0.4177636 
forest mean 861 : -0.4185247 
forest RMSE 861 : 0.0601806 

nnet 861 : -0.3183560 
nnet mean 861 : -0.3999435 
nnet RMSE 861 : 0.1484324 


s: 862 
logit 862 : -0.4205022 
logit mean 862 : -0.467956 
logit RMSE 862 : 0.08420369 

boosting 862 : -0.4276373 
boosting mean 862 : -0.4624965 
boosting RMSE 862 : 0.1578255 

forest 862 : -0.4291428 
forest mean 862 : -0.418537 
forest RMSE 862 : 0.06015387 

nnet 862 : -0.4300292 
nnet mean 862 : -0.3999784 
nnet RMSE 862 : 0.1483498 


s: 863 
logit 863 : -0.4803808 
logit mean 863 : -0.4679704 
logit RMSE 863 : 0.08419936 

boosting 863 : -0.5041665 
boosting mean 863 : -0.4625447 
boosting RMSE 863 : 0.1577738 

forest 863 : -0.5521528 
forest mean 863 : -0.4186918 
forest RMSE 863 : 0.0603417 

nnet 863 : -0.6159547 
nnet mean 863 : -0.4002286 
nnet RMSE 863 : 0.1484460 


s: 864 
logit 864 : -0.5220201 
logit mean 864 : -0.4680329 
logit RMSE 864 : 0.08425295 

boosting 864 : -0.5038607 
boosting mean 864 : -0.4625926 
boosting RMSE 864 : 0.1577221 

forest 864 : -0.4225562 
forest mean 864 : -0.4186963 
forest RMSE 864 : 0.06031165 

nnet 864 : -0.3206231 
nnet mean 864 : -0.4001365 
nnet RMSE 864 : 0.1483846 


s: 865 
logit 865 : -0.4413465 
logit mean 865 : -0.4680021 
logit RMSE 865 : 0.08421597 

boosting 865 : -0.3086488 
boosting mean 865 : -0.4624146 
boosting RMSE 865 : 0.1576615 

forest 865 : -0.3971272 
forest mean 865 : -0.4186714 
forest RMSE 865 : 0.06027686 

nnet 865 : -0.2456558 
nnet mean 865 : -0.3999579 
nnet RMSE 865 : 0.1483916 


s: 866 
logit 866 : -0.3841414 
logit mean 866 : -0.4679053 
logit RMSE 866 : 0.08416906 

boosting 866 : -0.6638434 
boosting mean 866 : -0.4626472 
boosting RMSE 866 : 0.1578253 

forest 866 : -0.4311705 
forest mean 866 : -0.4186858 
forest RMSE 866 : 0.06025136 

nnet 866 : -0.4158606 
nnet mean 866 : -0.3999763 
nnet RMSE 866 : 0.1483069 


s: 867 
logit 867 : -0.4877813 
logit mean 867 : -0.4679282 
logit RMSE 867 : 0.08417331 

boosting 867 : -0.3579542 
boosting mean 867 : -0.4625264 
boosting RMSE 867 : 0.1577407 

forest 867 : -0.4157075 
forest mean 867 : -0.4186824 
forest RMSE 867 : 0.06021896 

nnet 867 : -0.4359121 
nnet mean 867 : -0.4000177 
nnet RMSE 867 : 0.1482264 


s: 868 
logit 868 : -0.4705471 
logit mean 868 : -0.4679312 
logit RMSE 868 : 0.08415888 

boosting 868 : -0.2402277 
boosting mean 868 : -0.4622703 
boosting RMSE 868 : 0.1577431 

forest 868 : -0.3514878 
forest mean 868 : -0.4186049 
forest RMSE 868 : 0.06020678 

nnet 868 : -0.4929303 
nnet mean 868 : -0.4001248 
nnet RMSE 868 : 0.1481745 


s: 869 
logit 869 : -0.5496176 
logit mean 869 : -0.4680252 
logit RMSE 869 : 0.08426344 

boosting 869 : -0.365604 
boosting mean 869 : -0.4621591 
boosting RMSE 869 : 0.1576566 

forest 869 : -0.4374031 
forest mean 869 : -0.4186266 
forest RMSE 869 : 0.06018551 

nnet 869 : -0.353277 
nnet mean 869 : -0.4000709 
nnet RMSE 869 : 0.1480977 


s: 870 
logit 870 : -0.5478119 
logit mean 870 : -0.4681169 
logit RMSE 870 : 0.08436397 

boosting 870 : -0.3519402 
boosting mean 870 : -0.4620324 
boosting RMSE 870 : 0.1575744 

forest 870 : -0.4636445 
forest mean 870 : -0.4186783 
forest RMSE 870 : 0.0601896 

nnet 870 : -0.2893255 
nnet mean 870 : -0.3999436 
nnet RMSE 870 : 0.1480602 


s: 871 
logit 871 : -0.4788784 
logit mean 871 : -0.4681293 
logit RMSE 871 : 0.08435787 

boosting 871 : -0.4621044 
boosting mean 871 : -0.4620325 
boosting RMSE 871 : 0.157498 

forest 871 : -0.4433816 
forest mean 871 : -0.4187067 
forest RMSE 871 : 0.06017299 

nnet 871 : -0.2706355 
nnet mean 871 : -0.3997951 
nnet RMSE 871 : 0.1480400 


s: 872 
logit 872 : -0.3668857 
logit mean 872 : -0.4680132 
logit RMSE 872 : 0.08431695 

boosting 872 : -0.4335715 
boosting mean 872 : -0.4619998 
boosting RMSE 872 : 0.1574118 

forest 872 : -0.4075083 
forest mean 872 : -0.4186938 
forest RMSE 872 : 0.06013902 

nnet 872 : -0.4641817 
nnet mean 872 : -0.3998689 
nnet RMSE 872 : 0.1479711 


s: 873 
logit 873 : -0.4442778 
logit mean 873 : -0.467986 
logit RMSE 873 : 0.08428197 

boosting 873 : -0.4767416 
boosting mean 873 : -0.4620167 
boosting RMSE 873 : 0.1573430 

forest 873 : -0.3848808 
forest mean 873 : -0.4186551 
forest RMSE 873 : 0.06010674 

nnet 873 : -0.2048702 
nnet mean 873 : -0.3996456 
nnet RMSE 873 : 0.1480337 


s: 874 
logit 874 : -0.5352199 
logit mean 874 : -0.4680629 
logit RMSE 874 : 0.08435782 

boosting 874 : -0.6216442 
boosting mean 874 : -0.4621994 
boosting RMSE 874 : 0.1574316 

forest 874 : -0.4868787 
forest mean 874 : -0.4187332 
forest RMSE 874 : 0.06014418 

nnet 874 : -0.4091075 
nnet mean 874 : -0.3996564 
nnet RMSE 874 : 0.1479493 


s: 875 
logit 875 : -0.3458341 
logit mean 875 : -0.4679232 
logit RMSE 875 : 0.08432949 

boosting 875 : -0.4409444 
boosting mean 875 : -0.4621751 
boosting RMSE 875 : 0.1573477 

forest 875 : -0.3383103 
forest mean 875 : -0.4186413 
forest RMSE 875 : 0.06014597 

nnet 875 : -0.1890368 
nnet mean 875 : -0.3994157 
nnet RMSE 875 : 0.1480366 


s: 876 
logit 876 : -0.379549 
logit mean 876 : -0.4678223 
logit RMSE 876 : 0.08428417 

boosting 876 : -0.3483049 
boosting mean 876 : -0.4620451 
boosting RMSE 876 : 0.1572676 

forest 876 : -0.4111422 
forest mean 876 : -0.4186327 
forest RMSE 876 : 0.06011281 

nnet 876 : -0.5483788 
nnet mean 876 : -0.3995857 
nnet RMSE 876 : 0.1480370 


s: 877 
logit 877 : -0.4748146 
logit mean 877 : -0.4678303 
logit RMSE 877 : 0.08427398 

boosting 877 : -0.4382876 
boosting mean 877 : -0.462018 
boosting RMSE 877 : 0.1571832 

forest 877 : -0.4120611 
forest mean 877 : -0.4186252 
forest RMSE 877 : 0.06007991 

nnet 877 : -0.2429458 
nnet mean 877 : -0.3994071 
nnet RMSE 877 : 0.1480476 


s: 878 
logit 878 : -0.4905546 
logit mean 878 : -0.4678562 
logit RMSE 878 : 0.0842814 

boosting 878 : -0.5312623 
boosting mean 878 : -0.4620969 
boosting RMSE 878 : 0.1571561 

forest 878 : -0.4094483 
forest mean 878 : -0.4186147 
forest RMSE 878 : 0.06004653 

nnet 878 : -0.7902326 
nnet mean 878 : -0.3998523 
nnet RMSE 878 : 0.1485482 


s: 879 
logit 879 : -0.4521735 
logit mean 879 : -0.4678383 
logit RMSE 879 : 0.08425183 

boosting 879 : -0.3999023 
boosting mean 879 : -0.4620261 
boosting RMSE 879 : 0.1570667 

forest 879 : -0.4468607 
forest mean 879 : -0.4186469 
forest RMSE 879 : 0.06003318 

nnet 879 : -0.5876106 
nnet mean 879 : -0.4000659 
nnet RMSE 879 : 0.1485985 


s: 880 
logit 880 : -0.5783007 
logit mean 880 : -0.4679639 
logit RMSE 880 : 0.08441819 

boosting 880 : -0.4561076 
boosting mean 880 : -0.4620194 
boosting RMSE 880 : 0.1569888 

forest 880 : -0.4965101 
forest mean 880 : -0.4187354 
forest RMSE 880 : 0.0600872 

nnet 880 : -0.4371467 
nnet mean 880 : -0.400108 
nnet RMSE 880 : 0.1485193 


s: 881 
logit 881 : -0.4724458 
logit mean 881 : -0.4679690 
logit RMSE 881 : 0.08440556 

boosting 881 : -0.3559228 
boosting mean 881 : -0.461899 
boosting RMSE 881 : 0.1569067 

forest 881 : -0.4004726 
forest mean 881 : -0.4187146 
forest RMSE 881 : 0.06005309 

nnet 881 : -0.3645031 
nnet mean 881 : -0.4000676 
nnet RMSE 881 : 0.1484398 


s: 882 
logit 882 : -0.4847971 
logit mean 882 : -0.467988 
logit RMSE 882 : 0.084406 

boosting 882 : -0.431308 
boosting mean 882 : -0.4618643 
boosting RMSE 882 : 0.1568213 

forest 882 : -0.5093164 
forest mean 882 : -0.4188174 
forest RMSE 882 : 0.0601318 

nnet 882 : -0.2535658 
nnet mean 882 : -0.3999015 
nnet RMSE 882 : 0.1484376 


s: 883 
logit 883 : -0.4861058 
logit mean 883 : -0.4680085 
logit RMSE 883 : 0.08440795 

boosting 883 : -0.2820998 
boosting mean 883 : -0.4616607 
boosting RMSE 883 : 0.1567827 

forest 883 : -0.3724542 
forest mean 883 : -0.4187648 
forest RMSE 883 : 0.06010489 

nnet 883 : -0.477821 
nnet mean 883 : -0.3999897 
nnet RMSE 883 : 0.1483766 


s: 884 
logit 884 : -0.4211392 
logit mean 884 : -0.4679555 
logit RMSE 884 : 0.08436319 

boosting 884 : -0.4798231 
boosting mean 884 : -0.4616812 
boosting RMSE 884 : 0.1567170 

forest 884 : -0.4384823 
forest mean 884 : -0.4187872 
forest RMSE 884 : 0.06008483 

nnet 884 : -0.2334334 
nnet mean 884 : -0.3998013 
nnet RMSE 884 : 0.1483985 


s: 885 
logit 885 : -0.4999626 
logit mean 885 : -0.4679917 
logit RMSE 885 : 0.08438244 

boosting 885 : -0.2648512 
boosting mean 885 : -0.4614588 
boosting RMSE 885 : 0.1566943 

forest 885 : -0.3556684 
forest mean 885 : -0.4187158 
forest RMSE 885 : 0.06006936 

nnet 885 : -0.3518772 
nnet mean 885 : -0.3997472 
nnet RMSE 885 : 0.1483234 


s: 886 
logit 886 : -0.428918 
logit mean 886 : -0.4679476 
logit RMSE 886 : 0.0843404 

boosting 886 : -0.258545 
boosting mean 886 : -0.4612298 
boosting RMSE 886 : 0.1566779 

forest 886 : -0.4174885 
forest mean 886 : -0.4187144 
forest RMSE 886 : 0.06003832 

nnet 886 : -0.4066142 
nnet mean 886 : -0.3997549 
nnet RMSE 886 : 0.1482399 


s: 887 
logit 887 : -0.5009932 
logit mean 887 : -0.4679849 
logit RMSE 887 : 0.08436103 

boosting 887 : -0.294642 
boosting mean 887 : -0.461042 
boosting RMSE 887 : 0.1566295 

forest 887 : -0.2926608 
forest mean 887 : -0.4185723 
forest RMSE 887 : 0.06011261 

nnet 887 : -0.2629984 
nnet mean 887 : -0.3996007 
nnet RMSE 887 : 0.1482277 


s: 888 
logit 888 : -0.5473313 
logit mean 888 : -0.4680742 
logit RMSE 888 : 0.08445835 

boosting 888 : -0.437152 
boosting mean 888 : -0.4610151 
boosting RMSE 888 : 0.1565463 

forest 888 : -0.3995649 
forest mean 888 : -0.4185509 
forest RMSE 888 : 0.06007876 

nnet 888 : -0.3650322 
nnet mean 888 : -0.3995618 
nnet RMSE 888 : 0.1481488 


s: 889 
logit 889 : -0.4295551 
logit mean 889 : -0.4680309 
logit RMSE 889 : 0.08441666 

boosting 889 : -0.4454421 
boosting mean 889 : -0.4609976 
boosting RMSE 889 : 0.1564656 

forest 889 : -0.2806278 
forest mean 889 : -0.4183958 
forest RMSE 889 : 0.06017828 

nnet 889 : -0.3915188 
nnet mean 889 : -0.3995528 
nnet RMSE 889 : 0.1480657 


s: 890 
logit 890 : -0.4255081 
logit mean 890 : -0.4679831 
logit RMSE 890 : 0.08437355 

boosting 890 : -0.5512593 
boosting mean 890 : -0.461099 
boosting RMSE 890 : 0.1564599 

forest 890 : -0.3727076 
forest mean 890 : -0.4183445 
forest RMSE 890 : 0.06015142 

nnet 890 : -0.4522533 
nnet mean 890 : -0.399612 
nnet RMSE 890 : 0.1479929 


s: 891 
logit 891 : -0.4591805 
logit mean 891 : -0.4679732 
logit RMSE 891 : 0.0843495 

boosting 891 : -0.4512381 
boosting mean 891 : -0.4610879 
boosting RMSE 891 : 0.1563815 

forest 891 : -0.3763697 
forest mean 891 : -0.4182973 
forest RMSE 891 : 0.06012287 

nnet 891 : -0.3623507 
nnet mean 891 : -0.3995702 
nnet RMSE 891 : 0.1479152 


s: 892 
logit 892 : -0.494396 
logit mean 892 : -0.4680028 
logit RMSE 892 : 0.08436143 

boosting 892 : -0.497965 
boosting mean 892 : -0.4611293 
boosting RMSE 892 : 0.1563282 

forest 892 : -0.4017737 
forest mean 892 : -0.4182788 
forest RMSE 892 : 0.06008919 

nnet 892 : -0.4870077 
nnet mean 892 : -0.3996682 
nnet RMSE 892 : 0.1478610 


s: 893 
logit 893 : -0.4928657 
logit mean 893 : -0.4680307 
logit RMSE 893 : 0.08437143 

boosting 893 : -0.488554 
boosting mean 893 : -0.46116 
boosting RMSE 893 : 0.1562687 

forest 893 : -0.3677496 
forest mean 893 : -0.4182222 
forest RMSE 893 : 0.06006523 

nnet 893 : -0.4527438 
nnet mean 893 : -0.3997276 
nnet RMSE 893 : 0.1477887 


s: 894 
logit 894 : -0.4613645 
logit mean 894 : -0.4680232 
logit RMSE 894 : 0.0843492 

boosting 894 : -0.5405293 
boosting mean 894 : -0.4612488 
boosting RMSE 894 : 0.1562520 

forest 894 : -0.4012786 
forest mean 894 : -0.4182033 
forest RMSE 894 : 0.06003164 

nnet 894 : -0.2526498 
nnet mean 894 : -0.3995631 
nnet RMSE 894 : 0.1477882 


s: 895 
logit 895 : -0.4789482 
logit mean 895 : -0.4680354 
logit RMSE 895 : 0.08434336 

boosting 895 : -0.2092841 
boosting mean 895 : -0.4609672 
boosting RMSE 895 : 0.1562948 

forest 895 : -0.3805333 
forest mean 895 : -0.4181612 
forest RMSE 895 : 0.06000163 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 895 : -0.2665579 
nnet mean 895 : -0.3994145 
nnet RMSE 895 : 0.1477730 


s: 896 
logit 896 : -0.4872066 
logit mean 896 : -0.4680568 
logit RMSE 896 : 0.08434661 

boosting 896 : -0.5811651 
boosting mean 896 : -0.4611014 
boosting RMSE 896 : 0.1563247 

forest 896 : -0.4940829 
forest mean 896 : -0.4182459 
forest RMSE 896 : 0.06005045 

nnet 896 : -0.4606965 
nnet mean 896 : -0.3994829 
nnet RMSE 896 : 0.1477044 


s: 897 
logit 897 : -0.4850579 
logit mean 897 : -0.4680758 
logit RMSE 897 : 0.0843474 

boosting 897 : -0.5945035 
boosting mean 897 : -0.4612501 
boosting RMSE 897 : 0.1563725 

forest 897 : -0.479585 
forest mean 897 : -0.4183143 
forest RMSE 897 : 0.06007576 

nnet 897 : -0.6713231 
nnet mean 897 : -0.3997860 
nnet RMSE 897 : 0.1478998 


s: 898 
logit 898 : -0.4457868 
logit mean 898 : -0.468051 
logit RMSE 898 : 0.08431428 

boosting 898 : -0.4380813 
boosting mean 898 : -0.4612243 
boosting RMSE 898 : 0.1562906 

forest 898 : -0.3359567 
forest mean 898 : -0.4182226 
forest RMSE 898 : 0.06008032 

nnet 898 : -0.2639036 
nnet mean 898 : -0.3996346 
nnet RMSE 898 : 0.1478871 


s: 899 
logit 899 : -0.4326576 
logit mean 899 : -0.4680116 
logit RMSE 899 : 0.0842744 

boosting 899 : -0.5029727 
boosting mean 899 : -0.4612707 
boosting RMSE 899 : 0.1562414 

forest 899 : -0.4207097 
forest mean 899 : -0.4182254 
forest RMSE 899 : 0.06005087 

nnet 899 : -0.3754935 
nnet mean 899 : -0.3996078 
nnet RMSE 899 : 0.1478071 


s: 900 
logit 900 : -0.4947905 
logit mean 900 : -0.4680413 
logit RMSE 900 : 0.08428682 

boosting 900 : -0.2858177 
boosting mean 900 : -0.4610758 
boosting RMSE 900 : 0.1562009 

forest 900 : -0.3998972 
forest mean 900 : -0.418205 
forest RMSE 900 : 0.0600175 

nnet 900 : -0.3518866 
nnet mean 900 : -0.3995548 
nnet RMSE 900 : 0.1477337 


s: 901 
logit 901 : -0.497266 
logit mean 901 : -0.4680738 
logit RMSE 901 : 0.08430233 

boosting 901 : -0.3070645 
boosting mean 901 : -0.4609049 
boosting RMSE 901 : 0.1561449 

forest 901 : -0.3509651 
forest mean 901 : -0.4181304 
forest RMSE 901 : 0.06000643 

nnet 901 : -0.3615924 
nnet mean 901 : -0.3995126 
nnet RMSE 901 : 0.1476572 


s: 902 
logit 902 : -0.4467154 
logit mean 902 : -0.4680501 
logit RMSE 902 : 0.08426995 

boosting 902 : -0.4338905 
boosting mean 902 : -0.4608749 
boosting RMSE 902 : 0.1560624 

forest 902 : -0.3614371 
forest mean 902 : -0.4180675 
forest RMSE 902 : 0.0599869 

nnet 902 : -0.3607439 
nnet mean 902 : -0.3994696 
nnet RMSE 902 : 0.1475811 


s: 903 
logit 903 : -0.5024319 
logit mean 903 : -0.4680882 
logit RMSE 903 : 0.08429222 

boosting 903 : -0.4188534 
boosting mean 903 : -0.4608284 
boosting RMSE 903 : 0.1559772 

forest 903 : -0.454644 
forest mean 903 : -0.418108 
forest RMSE 903 : 0.05998124 

nnet 903 : -0.4026293 
nnet mean 903 : -0.3994731 
nnet RMSE 903 : 0.1474994 


s: 904 
logit 904 : -0.448109 
logit mean 904 : -0.4680661 
logit RMSE 904 : 0.08426078 

boosting 904 : -0.2254566 
boosting mean 904 : -0.460568 
boosting RMSE 904 : 0.155999 

forest 904 : -0.4692043 
forest mean 904 : -0.4181645 
forest RMSE 904 : 0.05999223 

nnet 904 : -0.5113464 
nnet mean 904 : -0.3995969 
nnet RMSE 904 : 0.1474643 


s: 905 
logit 905 : -0.4461902 
logit mean 905 : -0.4680419 
logit RMSE 905 : 0.08422821 

boosting 905 : -0.1488984 
boosting mean 905 : -0.4602236 
boosting RMSE 905 : 0.1561360 

forest 905 : -0.3833443 
forest mean 905 : -0.4181261 
forest RMSE 905 : 0.05996163 

nnet 905 : -0.2199471 
nnet mean 905 : -0.3993984 
nnet RMSE 905 : 0.1475043 


s: 906 
logit 906 : -0.4934433 
logit mean 906 : -0.4680699 
logit RMSE 906 : 0.08423894 

boosting 906 : -0.3418518 
boosting mean 906 : -0.460093 
boosting RMSE 906 : 0.1560618 

forest 906 : -0.4603057 
forest mean 906 : -0.4181726 
forest RMSE 906 : 0.05996201 

nnet 906 : -0.4731405 
nnet mean 906 : -0.3994798 
nnet RMSE 906 : 0.1474429 


s: 907 
logit 907 : -0.4262754 
logit mean 907 : -0.4680239 
logit RMSE 907 : 0.08419701 

boosting 907 : -0.5800075 
boosting mean 907 : -0.4602252 
boosting RMSE 907 : 0.1560902 

forest 907 : -0.4174635 
forest mean 907 : -0.4181718 
forest RMSE 907 : 0.05993175 

nnet 907 : -0.1114808 
nnet mean 907 : -0.3991623 
nnet RMSE 907 : 0.1476727 


s: 908 
logit 908 : -0.3847455 
logit mean 908 : -0.4679321 
logit RMSE 908 : 0.08415215 

boosting 908 : -0.3795137 
boosting mean 908 : -0.4601363 
boosting RMSE 908 : 0.1560057 

forest 908 : -0.4443801 
forest mean 908 : -0.4182007 
forest RMSE 908 : 0.05991685 

nnet 908 : -0.5080859 
nnet mean 908 : -0.3992822 
nnet RMSE 908 : 0.1476349 


s: 909 
logit 909 : -0.5092178 
logit mean 909 : -0.4679776 
logit RMSE 909 : 0.08418383 

boosting 909 : -0.4965652 
boosting mean 909 : -0.4601764 
boosting RMSE 909 : 0.1559528 

forest 909 : -0.3749328 
forest mean 909 : -0.4181531 
forest RMSE 909 : 0.05988965 

nnet 909 : -0.5276131 
nnet mean 909 : -0.3994234 
nnet RMSE 909 : 0.1476144 


s: 910 
logit 910 : -0.478816 
logit mean 910 : -0.4679895 
logit RMSE 910 : 0.08417812 

boosting 910 : -0.4681313 
boosting mean 910 : -0.4601851 
boosting RMSE 910 : 0.1558834 

forest 910 : -0.4150465 
forest mean 910 : -0.4181497 
forest RMSE 910 : 0.05985881 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 910 : -0.2488000 
nnet mean 910 : -0.3992579 
nnet RMSE 910 : 0.1476184 


s: 911 
logit 911 : -0.4609984 
logit mean 911 : -0.4679818 
logit RMSE 911 : 0.08415618 

boosting 911 : -0.4602775 
boosting mean 911 : -0.4601852 
boosting RMSE 911 : 0.1558107 

forest 911 : -0.4516356 
forest mean 911 : -0.4181865 
forest RMSE 911 : 0.05985041 

nnet 911 : -0.3730454 
nnet mean 911 : -0.3992291 
nnet RMSE 911 : 0.1475400 


s: 912 
logit 912 : -0.4545724 
logit mean 912 : -0.4679671 
logit RMSE 912 : 0.08412943 

boosting 912 : -0.5065207 
boosting mean 912 : -0.460236 
boosting RMSE 912 : 0.1557652 

forest 912 : -0.4504314 
forest mean 912 : -0.4182218 
forest RMSE 912 : 0.05984089 

nnet 912 : -0.4134052 
nnet mean 912 : -0.3992446 
nnet RMSE 912 : 0.1474598 


s: 913 
logit 913 : -0.5492324 
logit mean 913 : -0.4680561 
logit RMSE 913 : 0.08422827 

boosting 913 : -0.4064647 
boosting mean 913 : -0.4601771 
boosting RMSE 913 : 0.1556800 

forest 913 : -0.5039933 
forest mean 913 : -0.4183158 
forest RMSE 913 : 0.05990706 

nnet 913 : -0.2636088 
nnet mean 913 : -0.3990961 
nnet RMSE 913 : 0.1474481 


s: 914 
logit 914 : -0.4243236 
logit mean 914 : -0.4680083 
logit RMSE 914 : 0.08418603 

boosting 914 : -0.4622299 
boosting mean 914 : -0.4601794 
boosting RMSE 914 : 0.1556084 

forest 914 : -0.4671003 
forest mean 914 : -0.4183691 
forest RMSE 914 : 0.0599154 

nnet 914 : -0.06994932 
nnet mean 914 : -0.398736 
nnet RMSE 914 : 0.1477713 


s: 915 
logit 915 : -0.4490972 
logit mean 915 : -0.4679876 
logit RMSE 915 : 0.08415567 

boosting 915 : -0.2806869 
boosting mean 915 : -0.4599832 
boosting RMSE 915 : 0.1555734 

forest 915 : -0.3861433 
forest mean 915 : -0.4183339 
forest RMSE 915 : 0.0598844 

nnet 915 : -0.1819772 
nnet mean 915 : -0.3984991 
nnet RMSE 915 : 0.1478663 


s: 916 
logit 916 : -0.5101069 
logit mean 916 : -0.4680336 
logit RMSE 916 : 0.08418836 

boosting 916 : -0.5317125 
boosting mean 916 : -0.4600615 
boosting RMSE 916 : 0.1555493 

forest 916 : -0.3677083 
forest mean 916 : -0.4182786 
forest RMSE 916 : 0.05986121 

nnet 916 : -0.2855420 
nnet mean 916 : -0.3983758 
nnet RMSE 916 : 0.1478339 


s: 917 
logit 917 : -0.515264 
logit mean 917 : -0.4680851 
logit RMSE 917 : 0.0842285 

boosting 917 : -0.6923098 
boosting mean 917 : -0.4603148 
boosting RMSE 917 : 0.1557639 

forest 917 : -0.5444357 
forest mean 917 : -0.4184162 
forest RMSE 917 : 0.06001839 

nnet 917 : -0.5554145 
nnet mean 917 : -0.398547 
nnet RMSE 917 : 0.1478424 


s: 918 
logit 918 : -0.4156399 
logit mean 918 : -0.4680279 
logit RMSE 918 : 0.08418419 

boosting 918 : -0.5093662 
boosting mean 918 : -0.4603682 
boosting RMSE 918 : 0.1557208 

forest 918 : -0.3720534 
forest mean 918 : -0.4183657 
forest RMSE 918 : 0.05999278 

nnet 918 : -0.3869205 
nnet mean 918 : -0.3985343 
nnet RMSE 918 : 0.1477625 


s: 919 
logit 919 : -0.3851465 
logit mean 919 : -0.4679378 
logit RMSE 919 : 0.0841398 

boosting 919 : -0.7011053 
boosting mean 919 : -0.4606302 
boosting RMSE 919 : 0.1559527 

forest 919 : -0.4343091 
forest mean 919 : -0.4183831 
forest RMSE 919 : 0.05997081 

nnet 919 : -0.3630493 
nnet mean 919 : -0.3984957 
nnet RMSE 919 : 0.1476871 


s: 920 
logit 920 : -0.4571733 
logit mean 920 : -0.4679261 
logit RMSE 920 : 0.08411518 

boosting 920 : -0.4988124 
boosting mean 920 : -0.4606717 
boosting RMSE 920 : 0.1559020 

forest 920 : -0.4874421 
forest mean 920 : -0.4184581 
forest RMSE 920 : 0.0600075 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 920 : -0.2487201 
nnet mean 920 : -0.3983329 
nnet RMSE 920 : 0.1476910 


s: 921 
logit 921 : -0.5037711 
logit mean 921 : -0.467965 
logit RMSE 921 : 0.08413901 

boosting 921 : -0.2786794 
boosting mean 921 : -0.4604741 
boosting RMSE 921 : 0.1558686 

forest 921 : -0.3654622 
forest mean 921 : -0.4184006 
forest RMSE 921 : 0.05998571 

nnet 921 : -0.5039361 
nnet mean 921 : -0.3984476 
nnet RMSE 921 : 0.1476506 


s: 922 
logit 922 : -0.4644595 
logit mean 922 : -0.4679612 
logit RMSE 922 : 0.08412016 

boosting 922 : -0.4458677 
boosting mean 922 : -0.4604582 
boosting RMSE 922 : 0.1557914 

forest 922 : -0.3800347 
forest mean 922 : -0.418359 
forest RMSE 922 : 0.05995678 

nnet 922 : -0.1959386 
nnet mean 922 : -0.3982279 
nnet RMSE 922 : 0.1477234 


s: 923 
logit 923 : -0.4512086 
logit mean 923 : -0.467943 
logit RMSE 923 : 0.08409148 

boosting 923 : -0.636979 
boosting mean 923 : -0.4606495 
boosting RMSE 923 : 0.1559022 

forest 923 : -0.4330851 
forest mean 923 : -0.4183749 
forest RMSE 923 : 0.05993418 

nnet 923 : -0.2477307 
nnet mean 923 : -0.3980649 
nnet RMSE 923 : 0.1477284 


s: 924 
logit 924 : -0.4584701 
logit mean 924 : -0.4679328 
logit RMSE 924 : 0.08406797 

boosting 924 : -0.562275 
boosting mean 924 : -0.4607595 
boosting RMSE 924 : 0.1559092 

forest 924 : -0.4281541 
forest mean 924 : -0.4183855 
forest RMSE 924 : 0.0599089 

nnet 924 : -0.4942344 
nnet mean 924 : -0.398169 
nnet RMSE 924 : 0.147681 


s: 925 
logit 925 : -0.5247486 
logit mean 925 : -0.4679942 
logit RMSE 925 : 0.08412257 

boosting 925 : -0.5125088 
boosting mean 925 : -0.4608154 
boosting RMSE 925 : 0.1558689 

forest 925 : -0.4354457 
forest mean 925 : -0.4184040 
forest RMSE 925 : 0.05988785 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 925 : -0.2737616 
nnet mean 925 : -0.3980345 
nnet RMSE 925 : 0.1476595 


s: 926 
logit 926 : -0.4406804 
logit mean 926 : -0.4679647 
logit RMSE 926 : 0.08408776 

boosting 926 : -0.2302463 
boosting mean 926 : -0.4605664 
boosting RMSE 926 : 0.1558845 

forest 926 : -0.3316613 
forest mean 926 : -0.4183103 
forest RMSE 926 : 0.05989762 

nnet 926 : -0.4455302 
nnet mean 926 : -0.3980858 
nnet RMSE 926 : 0.1475873 


s: 927 
logit 927 : -0.4391808 
logit mean 927 : -0.4679337 
logit RMSE 927 : 0.08405225 

boosting 927 : -0.4804991 
boosting mean 927 : -0.4605879 
boosting RMSE 927 : 0.1558228 

forest 927 : -0.4427254 
forest mean 927 : -0.4183366 
forest RMSE 927 : 0.05988175 

nnet 927 : -0.3665708 
nnet mean 927 : -0.3980518 
nnet RMSE 927 : 0.1475118 


s: 928 
logit 928 : -0.3812509 
logit mean 928 : -0.4678402 
logit RMSE 928 : 0.0840092 

boosting 928 : -0.4139339 
boosting mean 928 : -0.4605376 
boosting RMSE 928 : 0.1557395 

forest 928 : -0.4750009 
forest mean 928 : -0.4183977 
forest RMSE 928 : 0.0599001 

nnet 928 : -0.4528071 
nnet mean 928 : -0.3981108 
nnet RMSE 928 : 0.1474425 


s: 929 
logit 929 : -0.4847732 
logit mean 929 : -0.4678585 
logit RMSE 929 : 0.08401003 

boosting 929 : -0.536835 
boosting mean 929 : -0.4606198 
boosting RMSE 929 : 0.1557204 

forest 929 : -0.3501815 
forest mean 929 : -0.4183242 
forest RMSE 929 : 0.05989016 

nnet 929 : -0.3064214 
nnet mean 929 : -0.3980121 
nnet RMSE 929 : 0.1473951 


s: 930 
logit 930 : -0.4326153 
logit mean 930 : -0.4678206 
logit RMSE 930 : 0.08397166 

boosting 930 : -0.5283154 
boosting mean 930 : -0.4606926 
boosting RMSE 930 : 0.1556935 

forest 930 : -0.4691729 
forest mean 930 : -0.4183789 
forest RMSE 930 : 0.05990091 

nnet 930 : -0.2952754 
nnet mean 930 : -0.3979016 
nnet RMSE 930 : 0.1473558 


s: 931 
logit 931 : -0.5262766 
logit mean 931 : -0.4678834 
logit RMSE 931 : 0.08402853 

boosting 931 : -0.4915449 
boosting mean 931 : -0.4607257 
boosting RMSE 931 : 0.1556388 

forest 931 : -0.4916218 
forest mean 931 : -0.4184576 
forest RMSE 931 : 0.05994399 

nnet 931 : -0.4413735 
nnet mean 931 : -0.3979483 
nnet RMSE 931 : 0.1472829 


s: 932 
logit 932 : -0.5523722 
logit mean 932 : -0.467974 
logit RMSE 932 : 0.08413162 

boosting 932 : -0.3364549 
boosting mean 932 : -0.4605924 
boosting RMSE 932 : 0.1555692 

forest 932 : -0.4061796 
forest mean 932 : -0.4184444 
forest RMSE 932 : 0.05991216 

nnet 932 : -0.2336423 
nnet mean 932 : -0.397772 
nnet RMSE 932 : 0.1473047 


s: 933 
logit 933 : -0.4431353 
logit mean 933 : -0.4679474 
logit RMSE 933 : 0.08409838 

boosting 933 : -0.5057856 
boosting mean 933 : -0.4606408 
boosting RMSE 933 : 0.1555244 

forest 933 : -0.457812 
forest mean 933 : -0.4184866 
forest RMSE 933 : 0.05990995 

nnet 933 : -0.3156870 
nnet mean 933 : -0.397684 
nnet RMSE 933 : 0.1472516 


s: 934 
logit 934 : -0.5160448 
logit mean 934 : -0.4679989 
logit RMSE 934 : 0.08413907 

boosting 934 : -0.4691262 
boosting mean 934 : -0.4606499 
boosting RMSE 934 : 0.1554576 

forest 934 : -0.4273993 
forest mean 934 : -0.4184962 
forest RMSE 934 : 0.05988458 

nnet 934 : -0.6752061 
nnet mean 934 : -0.3979812 
nnet RMSE 934 : 0.147448 


s: 935 
logit 935 : -0.4027399 
logit mean 935 : -0.4679291 
logit RMSE 935 : 0.0840941 

boosting 935 : -0.4119150 
boosting mean 935 : -0.4605978 
boosting RMSE 935 : 0.1553749 

forest 935 : -0.4725891 
forest mean 935 : -0.418554 
forest RMSE 935 : 0.05989961 

nnet 935 : -0.5365117 
nnet mean 935 : -0.3981293 
nnet RMSE 935 : 0.1474367 


s: 936 
logit 936 : -0.529306 
logit mean 936 : -0.4679947 
logit RMSE 936 : 0.08415537 

boosting 936 : -0.3899218 
boosting mean 936 : -0.4605222 
boosting RMSE 936 : 0.1552922 

forest 936 : -0.4208555 
forest mean 936 : -0.4185565 
forest RMSE 936 : 0.05987148 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 936 : -0.3751807 
nnet mean 936 : -0.3981048 
nnet RMSE 936 : 0.1473602 


s: 937 
logit 937 : -0.4761199 
logit mean 937 : -0.4680033 
logit RMSE 937 : 0.0841472 

boosting 937 : -0.4466988 
boosting mean 937 : -0.4605075 
boosting RMSE 937 : 0.1552168 

forest 937 : -0.4504139 
forest mean 937 : -0.4185905 
forest RMSE 937 : 0.05986219 

nnet 937 : -0.2999068 
nnet mean 937 : -0.398 
nnet RMSE 937 : 0.1473178 


s: 938 
logit 938 : -0.5180631 
logit mean 938 : -0.4680567 
logit RMSE 938 : 0.08419064 

boosting 938 : -0.4257173 
boosting mean 938 : -0.4604704 
boosting RMSE 938 : 0.1551364 

forest 938 : -0.4711682 
forest mean 938 : -0.4186465 
forest RMSE 938 : 0.05987538 

nnet 938 : -0.4016590 
nnet mean 938 : -0.3980039 
nnet RMSE 938 : 0.1472393 


s: 939 
logit 939 : -0.5008362 
logit mean 939 : -0.4680916 
logit RMSE 939 : 0.08421012 

boosting 939 : -0.5224057 
boosting mean 939 : -0.4605364 
boosting RMSE 939 : 0.1551052 

forest 939 : -0.5112289 
forest mean 939 : -0.4187451 
forest RMSE 939 : 0.05995347 

nnet 939 : -0.3320627 
nnet mean 939 : -0.3979337 
nnet RMSE 939 : 0.1471776 


s: 940 
logit 940 : -0.4607787 
logit mean 940 : -0.4680838 
logit RMSE 940 : 0.08418866 

boosting 940 : -0.3849418 
boosting mean 940 : -0.4604559 
boosting RMSE 940 : 0.1550234 

forest 940 : -0.4163802 
forest mean 940 : -0.4187426 
forest RMSE 940 : 0.05992395 

nnet 940 : -0.4384528 
nnet mean 940 : -0.3979768 
nnet RMSE 940 : 0.1471046 


s: 941 
logit 941 : -0.3829715 
logit mean 941 : -0.4679934 
logit RMSE 941 : 0.08414574 

boosting 941 : -0.5504297 
boosting mean 941 : -0.4605516 
boosting RMSE 941 : 0.1550186 

forest 941 : -0.459826 
forest mean 941 : -0.4187863 
forest RMSE 941 : 0.05992385 

nnet 941 : -0.5931087 
nnet mean 941 : -0.3981842 
nnet RMSE 941 : 0.1471611 


s: 942 
logit 942 : -0.4689208 
logit mean 942 : -0.4679944 
logit RMSE 942 : 0.08413104 

boosting 942 : -0.1253565 
boosting mean 942 : -0.4601957 
boosting RMSE 942 : 0.1551945 

forest 942 : -0.419559 
forest mean 942 : -0.4187871 
forest RMSE 942 : 0.05989542 

nnet 942 : -0.3585654 
nnet mean 942 : -0.3981421 
nnet RMSE 942 : 0.1470892 


s: 943 
logit 943 : -0.4222278 
logit mean 943 : -0.4679458 
logit RMSE 943 : 0.08408954 

boosting 943 : -0.5518813 
boosting mean 943 : -0.4602930 
boosting RMSE 943 : 0.1551910 

forest 943 : -0.3633314 
forest mean 943 : -0.4187283 
forest RMSE 943 : 0.05987556 

nnet 943 : -0.06266105 
nnet mean 943 : -0.3977863 
nnet RMSE 943 : 0.1474211 


s: 944 
logit 944 : -0.4437849 
logit mean 944 : -0.4679202 
logit RMSE 944 : 0.08405707 

boosting 944 : -0.2842436 
boosting mean 944 : -0.4601065 
boosting RMSE 944 : 0.1551546 

forest 944 : -0.5622609 
forest mean 944 : -0.4188803 
forest RMSE 944 : 0.06007642 

nnet 944 : -0.3273428 
nnet mean 944 : -0.3977117 
nnet RMSE 944 : 0.1473619 


s: 945 
logit 945 : -0.4503511 
logit mean 945 : -0.4679017 
logit RMSE 945 : 0.08402854 

boosting 945 : -0.3961994 
boosting mean 945 : -0.4600388 
boosting RMSE 945 : 0.1550725 

forest 945 : -0.4055695 
forest mean 945 : -0.4188662 
forest RMSE 945 : 0.0600449 

nnet 945 : -0.5266959 
nnet mean 945 : -0.3978482 
nnet RMSE 945 : 0.1473416 


s: 946 
logit 946 : -0.5217696 
logit mean 946 : -0.4679586 
logit RMSE 946 : 0.08407738 

boosting 946 : -0.2994409 
boosting mean 946 : -0.4598691 
boosting RMSE 946 : 0.155025 

forest 946 : -0.4617957 
forest mean 946 : -0.4189116 
forest RMSE 946 : 0.06004677 

nnet 946 : -0.47754 
nnet mean 946 : -0.3979324 
nnet RMSE 946 : 0.1472853 


s: 947 
logit 947 : -0.512969 
logit mean 947 : -0.4680061 
logit RMSE 947 : 0.08411313 

boosting 947 : -0.4877841 
boosting mean 947 : -0.4598985 
boosting RMSE 947 : 0.1549694 

forest 947 : -0.5382107 
forest mean 947 : -0.4190376 
forest RMSE 947 : 0.06018288 

nnet 947 : -0.479061 
nnet mean 947 : -0.3980181 
nnet RMSE 947 : 0.1472299 


s: 948 
logit 948 : -0.4194569 
logit mean 948 : -0.4679549 
logit RMSE 948 : 0.08407113 

boosting 948 : -0.4742615 
boosting mean 948 : -0.4599137 
boosting RMSE 948 : 0.1549064 

forest 948 : -0.4658926 
forest mean 948 : -0.419087 
forest RMSE 948 : 0.06018919 

nnet 948 : -0.376783 
nnet mean 948 : -0.3979957 
nnet RMSE 948 : 0.1471542 


s: 949 
logit 949 : -0.4724894 
logit mean 949 : -0.4679597 
logit RMSE 949 : 0.08405976 

boosting 949 : -0.3670057 
boosting mean 949 : -0.4598158 
boosting RMSE 949 : 0.1548285 

forest 949 : -0.3422158 
forest mean 949 : -0.419006 
forest RMSE 949 : 0.0601867 

nnet 949 : -0.6666026 
nnet mean 949 : -0.3982788 
nnet RMSE 949 : 0.147331 


s: 950 
logit 950 : -0.3853218 
logit mean 950 : -0.4678727 
logit RMSE 950 : 0.08401686 

boosting 950 : -0.3710462 
boosting mean 950 : -0.4597224 
boosting RMSE 950 : 0.1547498 

forest 950 : -0.3926616 
forest mean 950 : -0.4189783 
forest RMSE 950 : 0.06015549 

nnet 950 : -0.6861969 
nnet mean 950 : -0.3985818 
nnet RMSE 950 : 0.1475459 


s: 951 
logit 951 : -0.3991335 
logit mean 951 : -0.4678004 
logit RMSE 951 : 0.08397268 

boosting 951 : -0.3105729 
boosting mean 951 : -0.4595655 
boosting RMSE 951 : 0.1546956 

forest 951 : -0.4417807 
forest mean 951 : -0.4190023 
forest RMSE 951 : 0.06013912 

nnet 951 : -0.1842062 
nnet mean 951 : -0.3983564 
nnet RMSE 951 : 0.1476342 


s: 952 
logit 952 : -0.4149147 
logit mean 952 : -0.4677449 
logit RMSE 952 : 0.08392996 

boosting 952 : -0.2074852 
boosting mean 952 : -0.4593007 
boosting RMSE 952 : 0.1547402 

forest 952 : -0.3649554 
forest mean 952 : -0.4189455 
forest RMSE 952 : 0.06011825 

nnet 952 : -0.1624535 
nnet mean 952 : -0.3981086 
nnet RMSE 952 : 0.1477574 


s: 953 
logit 953 : -0.3980029 
logit mean 953 : -0.4676717 
logit RMSE 953 : 0.08388594 

boosting 953 : -0.2052883 
boosting mean 953 : -0.4590342 
boosting RMSE 953 : 0.1547875 

forest 953 : -0.4114122 
forest mean 953 : -0.4189376 
forest RMSE 953 : 0.06008784 

nnet 953 : -0.1378476 
nnet mean 953 : -0.3978355 
nnet RMSE 953 : 0.1479238 


s: 954 
logit 954 : -0.5826062 
logit mean 954 : -0.4677922 
logit RMSE 954 : 0.08405014 

boosting 954 : -0.4065638 
boosting mean 954 : -0.4589792 
boosting RMSE 954 : 0.1547065 

forest 954 : -0.4156083 
forest mean 954 : -0.4189341 
forest RMSE 954 : 0.06005846 

nnet 954 : -0.2554664 
nnet mean 954 : -0.3976863 
nnet RMSE 954 : 0.1479203 


s: 955 
logit 955 : -0.553979 
logit mean 955 : -0.4678824 
logit RMSE 955 : 0.08415377 

boosting 955 : -0.5414611 
boosting mean 955 : -0.4590656 
boosting RMSE 955 : 0.1546933 

forest 955 : -0.433883 
forest mean 955 : -0.4189497 
forest RMSE 955 : 0.06003702 

nnet 955 : -0.3028880 
nnet mean 955 : -0.397587 
nnet RMSE 955 : 0.1478762 


s: 956 
logit 956 : -0.4780257 
logit mean 956 : -0.467893 
logit RMSE 956 : 0.08414759 

boosting 956 : -0.9707526 
boosting mean 956 : -0.4596008 
boosting RMSE 956 : 0.1557104 

forest 956 : -0.4492438 
forest mean 956 : -0.4189814 
forest RMSE 956 : 0.06002675 

nnet 956 : -0.5514907 
nnet mean 956 : -0.397748 
nnet RMSE 956 : 0.1478801 


s: 957 
logit 957 : -0.5527897 
logit mean 957 : -0.4679817 
logit RMSE 957 : 0.08424851 

boosting 957 : -0.2541249 
boosting mean 957 : -0.4593861 
boosting RMSE 957 : 0.1557004 

forest 957 : -0.4658918 
forest mean 957 : -0.4190305 
forest RMSE 957 : 0.06003318 

nnet 957 : -0.602071 
nnet mean 957 : -0.3979615 
nnet RMSE 957 : 0.1479470 


s: 958 
logit 958 : -0.3761455 
logit mean 958 : -0.4678859 
logit RMSE 958 : 0.08420805 

boosting 958 : -0.4023439 
boosting mean 958 : -0.4593265 
boosting RMSE 958 : 0.1556192 

forest 958 : -0.3856443 
forest mean 958 : -0.4189956 
forest RMSE 958 : 0.06000363 

nnet 958 : -0.1961383 
nnet mean 958 : -0.3977508 
nnet RMSE 958 : 0.1480164 


s: 959 
logit 959 : -0.4378284 
logit mean 959 : -0.4678545 
logit RMSE 959 : 0.084173 

boosting 959 : -0.6987663 
boosting mean 959 : -0.4595762 
boosting RMSE 959 : 0.1558369 

forest 959 : -0.3686548 
forest mean 959 : -0.4189431 
forest RMSE 959 : 0.05998088 

nnet 959 : -0.4916776 
nnet mean 959 : -0.3978488 
nnet RMSE 959 : 0.1479688 


s: 960 
logit 960 : -0.4805842 
logit mean 960 : -0.4678678 
logit RMSE 960 : 0.08416934 

boosting 960 : -0.3160889 
boosting mean 960 : -0.4594268 
boosting RMSE 960 : 0.1557793 

forest 960 : -0.3994215 
forest mean 960 : -0.4189228 
forest RMSE 960 : 0.05994963 

nnet 960 : -0.3567129 
nnet mean 960 : -0.3978059 
nnet RMSE 960 : 0.1478984 


s: 961 
logit 961 : -0.4593461 
logit mean 961 : -0.4678589 
logit RMSE 961 : 0.08414732 

boosting 961 : -0.4121576 
boosting mean 961 : -0.4593776 
boosting RMSE 961 : 0.1556987 

forest 961 : -0.4811389 
forest mean 961 : -0.4189875 
forest RMSE 961 : 0.05997557 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 961 : -0.2284616 
nnet mean 961 : -0.3976297 
nnet RMSE 961 : 0.1479249 


s: 962 
logit 962 : -0.4250092 
logit mean 962 : -0.4678144 
logit RMSE 962 : 0.08410744 

boosting 962 : -0.4519175 
boosting mean 962 : -0.4593698 
boosting RMSE 962 : 0.1556268 

forest 962 : -0.4236047 
forest mean 962 : -0.4189923 
forest RMSE 962 : 0.05994922 

nnet 962 : -0.4574648 
nnet mean 962 : -0.3976919 
nnet RMSE 962 : 0.1478596 


s: 963 
logit 963 : -0.3944381 
logit mean 963 : -0.4677382 
logit RMSE 963 : 0.08406395 

boosting 963 : -0.5067256 
boosting mean 963 : -0.459419 
boosting RMSE 963 : 0.1555840 

forest 963 : -0.4255352 
forest mean 963 : -0.4189991 
forest RMSE 963 : 0.05992374 

nnet 963 : -0.4597823 
nnet mean 963 : -0.3977564 
nnet RMSE 963 : 0.1477954 


s: 964 
logit 964 : -0.4602359 
logit mean 964 : -0.4677304 
logit RMSE 964 : 0.08404273 

boosting 964 : -0.4176279 
boosting mean 964 : -0.4593756 
boosting RMSE 964 : 0.1555043 

forest 964 : -0.4528657 
forest mean 964 : -0.4190342 
forest RMSE 964 : 0.05991685 

nnet 964 : -0.2578321 
nnet mean 964 : -0.3976112 
nnet RMSE 964 : 0.1477897 


s: 965 
logit 965 : -0.4131297 
logit mean 965 : -0.4676738 
logit RMSE 965 : 0.08400024 

boosting 965 : -0.3422274 
boosting mean 965 : -0.4592542 
boosting RMSE 965 : 0.1554348 

forest 965 : -0.3474178 
forest mean 965 : -0.41896 
forest RMSE 965 : 0.05990971 

nnet 965 : -0.612161 
nnet mean 965 : -0.3978336 
nnet RMSE 965 : 0.1478709 


s: 966 
logit 966 : -0.5014303 
logit mean 966 : -0.4677088 
logit RMSE 966 : 0.08402015 

boosting 966 : -0.4988833 
boosting mean 966 : -0.4592953 
boosting RMSE 966 : 0.1553869 

forest 966 : -0.4707446 
forest mean 966 : -0.4190136 
forest RMSE 966 : 0.05992194 

nnet 966 : -0.4183527 
nnet mean 966 : -0.3978548 
nnet RMSE 966 : 0.1477955 


s: 967 
logit 967 : -0.4456149 
logit mean 967 : -0.4676859 
logit RMSE 967 : 0.0839895 

boosting 967 : -0.3085951 
boosting mean 967 : -0.4591394 
boosting RMSE 967 : 0.1553344 

forest 967 : -0.4435822 
forest mean 967 : -0.419039 
forest RMSE 967 : 0.05990734 

nnet 967 : -0.5490561 
nnet mean 967 : -0.3980112 
nnet RMSE 967 : 0.1477968 


s: 968 
logit 968 : -0.4080782 
logit mean 968 : -0.4676243 
logit RMSE 968 : 0.08394651 

boosting 968 : -0.4067739 
boosting mean 968 : -0.4590853 
boosting RMSE 968 : 0.1552543 

forest 968 : -0.4034832 
forest mean 968 : -0.419023 
forest RMSE 968 : 0.0598765 

nnet 968 : -0.5009167 
nnet mean 968 : -0.3981175 
nnet RMSE 968 : 0.1477561 


s: 969 
logit 969 : -0.4097379 
logit mean 969 : -0.4675646 
logit RMSE 969 : 0.08390377 

boosting 969 : -0.4016565 
boosting mean 969 : -0.4590261 
boosting RMSE 969 : 0.1551741 

forest 969 : -0.4180672 
forest mean 969 : -0.419022 
forest RMSE 969 : 0.05984841 

nnet 969 : -0.4038131 
nnet mean 969 : -0.3981234 
nnet RMSE 969 : 0.1476798 


s: 970 
logit 970 : -0.4656961 
logit mean 970 : -0.4675627 
logit RMSE 970 : 0.08388703 

boosting 970 : -0.5749722 
boosting mean 970 : -0.4591456 
boosting RMSE 970 : 0.1551958 

forest 970 : -0.4458359 
forest mean 970 : -0.4190496 
forest RMSE 970 : 0.05983565 

nnet 970 : -0.5266111 
nnet mean 970 : -0.3982558 
nnet RMSE 970 : 0.1476597 


s: 971 
logit 971 : -0.4296053 
logit mean 971 : -0.4675236 
logit RMSE 971 : 0.0838492 

boosting 971 : -0.4897275 
boosting mean 971 : -0.4591771 
boosting RMSE 971 : 0.1551426 

forest 971 : -0.5108132 
forest mean 971 : -0.4191441 
forest RMSE 971 : 0.05991047 

nnet 971 : -0.3146693 
nnet mean 971 : -0.3981697 
nnet RMSE 971 : 0.1476090 


s: 972 
logit 972 : -0.4515252 
logit mean 972 : -0.4675071 
logit RMSE 972 : 0.08382236 

boosting 972 : -0.2320645 
boosting mean 972 : -0.4589434 
boosting RMSE 972 : 0.1551563 

forest 972 : -0.4192544 
forest mean 972 : -0.4191442 
forest RMSE 972 : 0.05988283 

nnet 972 : -0.3697078 
nnet mean 972 : -0.3981405 
nnet RMSE 972 : 0.1475363 


s: 973 
logit 973 : -0.4056491 
logit mean 973 : -0.4674436 
logit RMSE 973 : 0.08377947 

boosting 973 : -0.5091692 
boosting mean 973 : -0.4589950 
boosting RMSE 973 : 0.1551161 

forest 973 : -0.364991 
forest mean 973 : -0.4190886 
forest RMSE 973 : 0.05986257 

nnet 973 : -0.09784664 
nnet mean 973 : -0.3978318 
nnet RMSE 973 : 0.1477782 


s: 974 
logit 974 : -0.4820666 
logit mean 974 : -0.4674586 
logit RMSE 974 : 0.08377773 

boosting 974 : -0.3044791 
boosting mean 974 : -0.4588364 
boosting RMSE 974 : 0.1550666 

forest 974 : -0.4173768 
forest mean 974 : -0.4190868 
forest RMSE 974 : 0.05983442 

nnet 974 : -0.3333926 
nnet mean 974 : -0.3977657 
nnet RMSE 974 : 0.1477178 


s: 975 
logit 975 : -0.5251095 
logit mean 975 : -0.4675177 
logit RMSE 975 : 0.08383056 

boosting 975 : -0.4742883 
boosting mean 975 : -0.4588523 
boosting RMSE 975 : 0.1550054 

forest 975 : -0.4635031 
forest mean 975 : -0.4191324 
forest RMSE 975 : 0.0598383 

nnet 975 : -0.3215807 
nnet mean 975 : -0.3976875 
nnet RMSE 975 : 0.1476634 


s: 976 
logit 976 : -0.5266857 
logit mean 976 : -0.4675783 
logit RMSE 976 : 0.08388567 

boosting 976 : -0.5148488 
boosting mean 976 : -0.4589096 
boosting RMSE 976 : 0.1549695 

forest 976 : -0.4000799 
forest mean 976 : -0.4191129 
forest RMSE 976 : 0.05980764 

nnet 976 : -0.4370726 
nnet mean 976 : -0.3977279 
nnet RMSE 976 : 0.1475925 


s: 977 
logit 977 : -0.4516644 
logit mean 977 : -0.467562 
logit RMSE 977 : 0.08385902 

boosting 977 : -0.4875682 
boosting mean 977 : -0.458939 
boosting RMSE 977 : 0.1549155 

forest 977 : -0.4476376 
forest mean 977 : -0.4191421 
forest RMSE 977 : 0.05979645 

nnet 977 : -0.335485 
nnet mean 977 : -0.3976642 
nnet RMSE 977 : 0.1475314 


s: 978 
logit 978 : -0.4380695 
logit mean 978 : -0.4675319 
logit RMSE 978 : 0.08382498 

boosting 978 : -0.4366944 
boosting mean 978 : -0.4589162 
boosting RMSE 978 : 0.1548408 

forest 978 : -0.3463218 
forest mean 978 : -0.4190676 
forest RMSE 978 : 0.05979051 

nnet 978 : -0.6429432 
nnet mean 978 : -0.397915 
nnet RMSE 978 : 0.1476604 


s: 979 
logit 979 : -0.5052737 
logit mean 979 : -0.4675704 
logit RMSE 979 : 0.08384969 

boosting 979 : -0.6727471 
boosting mean 979 : -0.4591346 
boosting RMSE 979 : 0.1550070 

forest 979 : -0.3805557 
forest mean 979 : -0.4190283 
forest RMSE 979 : 0.0597632 

nnet 979 : -0.3342733 
nnet mean 979 : -0.39785 
nnet RMSE 979 : 0.1475999 


s: 980 
logit 980 : -0.497761 
logit mean 980 : -0.4676012 
logit RMSE 980 : 0.08386506 

boosting 980 : -0.4691642 
boosting mean 980 : -0.4591449 
boosting RMSE 980 : 0.1549436 

forest 980 : -0.3892289 
forest mean 980 : -0.4189979 
forest RMSE 980 : 0.05973369 

nnet 980 : -0.415116 
nnet mean 980 : -0.3978676 
nnet RMSE 980 : 0.1475254 


s: 981 
logit 981 : -0.4501956 
logit mean 981 : -0.4675835 
logit RMSE 981 : 0.08383762 

boosting 981 : -0.4406362 
boosting mean 981 : -0.459126 
boosting RMSE 981 : 0.1548701 

forest 981 : -0.4607666 
forest mean 981 : -0.4190404 
forest RMSE 981 : 0.05973475 

nnet 981 : -0.3272720 
nnet mean 981 : -0.3977956 
nnet RMSE 981 : 0.1474685 


s: 982 
logit 982 : -0.4060334 
logit mean 982 : -0.4675208 
logit RMSE 982 : 0.08379515 

boosting 982 : -0.3535411 
boosting mean 982 : -0.4590185 
boosting RMSE 982 : 0.1547983 

forest 982 : -0.4908304 
forest mean 982 : -0.4191135 
forest RMSE 982 : 0.05977465 

nnet 982 : -0.3841177 
nnet mean 982 : -0.3977817 
nnet RMSE 982 : 0.1473942 


s: 983 
logit 983 : -0.5703924 
logit mean 983 : -0.4676255 
logit RMSE 983 : 0.08392866 

boosting 983 : -0.3553988 
boosting mean 983 : -0.4589131 
boosting RMSE 983 : 0.1547261 

forest 983 : -0.4237595 
forest mean 983 : -0.4191183 
forest RMSE 983 : 0.05974904 

nnet 983 : -0.2461014 
nnet mean 983 : -0.3976274 
nnet RMSE 983 : 0.147401 


s: 984 
logit 984 : -0.3537031 
logit mean 984 : -0.4675097 
logit RMSE 984 : 0.08389898 

boosting 984 : -0.5016894 
boosting mean 984 : -0.4589565 
boosting RMSE 984 : 0.1546814 

forest 984 : -0.3228965 
forest mean 984 : -0.4190205 
forest RMSE 984 : 0.05976923 

nnet 984 : -0.4939181 
nnet mean 984 : -0.3977252 
nnet RMSE 984 : 0.1473565 


s: 985 
logit 985 : -0.4808089 
logit mean 985 : -0.4675232 
logit RMSE 985 : 0.0838959 

boosting 985 : -0.4474581 
boosting mean 985 : -0.4589449 
boosting RMSE 985 : 0.1546103 

forest 985 : -0.4524702 
forest mean 985 : -0.4190544 
forest RMSE 985 : 0.05976228 

nnet 985 : -0.3853587 
nnet mean 985 : -0.3977127 
nnet RMSE 985 : 0.1472824 


s: 986 
logit 986 : -0.4646006 
logit mean 986 : -0.4675202 
logit RMSE 986 : 0.08387858 

boosting 986 : -0.4277612 
boosting mean 986 : -0.4589132 
boosting RMSE 986 : 0.1545344 

forest 986 : -0.4322165 
forest mean 986 : -0.4190678 
forest RMSE 986 : 0.05974077 

nnet 986 : -0.640469 
nnet mean 986 : -0.3979589 
nnet RMSE 986 : 0.1474068 


s: 987 
logit 987 : -0.3563594 
logit mean 987 : -0.4674076 
logit RMSE 987 : 0.08384759 

boosting 987 : -0.2535838 
boosting mean 987 : -0.4587052 
boosting RMSE 987 : 0.1545263 

forest 987 : -0.3971061 
forest mean 987 : -0.4190455 
forest RMSE 987 : 0.05971057 

nnet 987 : -0.2142101 
nnet mean 987 : -0.3977727 
nnet RMSE 987 : 0.1474507 


s: 988 
logit 988 : -0.4646934 
logit mean 988 : -0.4674049 
logit RMSE 988 : 0.08383041 

boosting 988 : -0.5291279 
boosting mean 988 : -0.4587765 
boosting RMSE 988 : 0.1545028 

forest 988 : -0.4181092 
forest mean 988 : -0.4190446 
forest RMSE 988 : 0.05968313 

nnet 988 : -0.480378 
nnet mean 988 : -0.3978563 
nnet RMSE 988 : 0.1473983 


s: 989 
logit 989 : -0.403989 
logit mean 989 : -0.4673407 
logit RMSE 989 : 0.08378811 

boosting 989 : -0.3585699 
boosting mean 989 : -0.4586752 
boosting RMSE 989 : 0.1544302 

forest 989 : -0.3129663 
forest mean 989 : -0.4189373 
forest RMSE 989 : 0.05971711 

nnet 989 : -0.4962358 
nnet mean 989 : -0.3979558 
nnet RMSE 989 : 0.1473555 


s: 990 
logit 990 : -0.5598204 
logit mean 990 : -0.4674341 
logit RMSE 990 : 0.08389969 

boosting 990 : -0.470059 
boosting mean 990 : -0.4586867 
boosting RMSE 990 : 0.1543683 

forest 990 : -0.408242 
forest mean 990 : -0.4189265 
forest RMSE 990 : 0.05968752 

nnet 990 : -0.1897016 
nnet mean 990 : -0.3977454 
nnet RMSE 990 : 0.1474326 


s: 991 
logit 991 : -0.4521333 
logit mean 991 : -0.4674187 
logit RMSE 991 : 0.0838737 

boosting 991 : -0.4711708 
boosting mean 991 : -0.4586993 
boosting RMSE 991 : 0.1543069 

forest 991 : -0.3300722 
forest mean 991 : -0.4188369 
forest RMSE 991 : 0.05969874 

nnet 991 : -0.4111614 
nnet mean 991 : -0.397759 
nnet RMSE 991 : 0.1473587 


s: 992 
logit 992 : -0.4411608 
logit mean 992 : -0.4673922 
logit RMSE 992 : 0.0838416 

boosting 992 : -0.2579487 
boosting mean 992 : -0.4584969 
boosting RMSE 992 : 0.1542951 

forest 992 : -0.4256372 
forest mean 992 : -0.4188437 
forest RMSE 992 : 0.05967419 

nnet 992 : -0.2986094 
nnet mean 992 : -0.397659 
nnet RMSE 992 : 0.1473195 


s: 993 
logit 993 : -0.4932226 
logit mean 993 : -0.4674182 
logit RMSE 993 : 0.08385157 

boosting 993 : -0.3177764 
boosting mean 993 : -0.4583552 
boosting RMSE 993 : 0.1542394 

forest 993 : -0.4130718 
forest mean 993 : -0.4188379 
forest RMSE 993 : 0.05964558 

nnet 993 : -0.2036494 
nnet mean 993 : -0.3974637 
nnet RMSE 993 : 0.1473771 


s: 994 
logit 994 : -0.3837255 
logit mean 994 : -0.4673340 
logit RMSE 994 : 0.08381097 

boosting 994 : -0.1970178 
boosting mean 994 : -0.4580923 
boosting RMSE 994 : 0.1542962 

forest 994 : -0.4884191 
forest mean 994 : -0.4189079 
forest RMSE 994 : 0.0596815 

nnet 994 : -0.2652365 
nnet mean 994 : -0.3973306 
nnet RMSE 994 : 0.1473650 


s: 995 
logit 995 : -0.4462731 
logit mean 995 : -0.4673129 
logit RMSE 995 : 0.08378169 

boosting 995 : -0.3478562 
boosting mean 995 : -0.4579815 
boosting RMSE 995 : 0.1542275 

forest 995 : -0.4568224 
forest mean 995 : -0.418946 
forest RMSE 995 : 0.05967869 

nnet 995 : -0.3762080 
nnet mean 995 : -0.3973094 
nnet RMSE 995 : 0.1472928 


s: 996 
logit 996 : -0.4046351 
logit mean 996 : -0.4672500 
logit RMSE 996 : 0.08373975 

boosting 996 : -0.4544942 
boosting mean 996 : -0.457978 
boosting RMSE 996 : 0.1541597 

forest 996 : -0.4260266 
forest mean 996 : -0.4189531 
forest RMSE 996 : 0.05965443 

nnet 996 : -0.4474189 
nnet mean 996 : -0.3973597 
nnet RMSE 996 : 0.1472265 


s: 997 
logit 997 : -0.5208389 
logit mean 997 : -0.4673037 
logit RMSE 997 : 0.08378519 

boosting 997 : -0.5500768 
boosting mean 997 : -0.4580703 
boosting RMSE 997 : 0.1541557 

forest 997 : -0.4619678 
forest mean 997 : -0.4189963 
forest RMSE 997 : 0.05965679 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 997 : -0.25787 
nnet mean 997 : -0.3972198 
nnet RMSE 997 : 0.1472215 


s: 998 
logit 998 : -0.4695484 
logit mean 998 : -0.4673060 
logit RMSE 998 : 0.08377213 

boosting 998 : -0.4228852 
boosting mean 998 : -0.4580351 
boosting RMSE 998 : 0.1540802 

forest 998 : -0.4924324 
forest mean 998 : -0.4190699 
forest RMSE 998 : 0.05969864 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 998 : -0.308888 
nnet mean 998 : -0.3971313 
nnet RMSE 998 : 0.147176 


s: 999 
logit 999 : -0.3836712 
logit mean 999 : -0.4672222 
logit RMSE 999 : 0.08373179 

boosting 999 : -0.4665956 
boosting mean 999 : -0.4580437 
boosting RMSE 999 : 0.1540174 

forest 999 : -0.4045178 
forest mean 999 : -0.4190553 
forest RMSE 999 : 0.05966892 

nnet 999 : -0.3687017 
nnet mean 999 : -0.3971028 
nnet RMSE 999 : 0.1471057 


s: 1000 
logit 1000 : -0.4207188 
logit mean 1000 : -0.4671757 
logit RMSE 1000 : 0.08369248 

boosting 1000 : -0.2780074 
boosting mean 1000 : -0.4578636 
boosting RMSE 1000 : 0.1539887 

forest 1000 : -0.3948645 
forest mean 1000 : -0.4190311 
forest RMSE 1000 : 0.0596393 

nnet 1000 : -0.3338291 
nnet mean 1000 : -0.3970396 
nnet RMSE 1000 : 0.1470470 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> rm(sdta)
> save.image("RData.sims.G.nobs1000",compress="bzip2")
> 
> proc.time()
    user   system  elapsed 
46374.69    11.04 48062.51 
